feat(python): add native distribution and release infrastructure

- add the Rust-backed Python API with PyStemmer compatibility - distribute standard compiled models as a separate Python package - generate model artifacts during builds instead of storing them in Git - add GitHub release and Pages-backed package index workflows - add Python tests, benchmarks, documentation, and Gradle integration - refresh the documentation site, branding, and language benchmarks
2026-08-10 22:34:32 +02:00
parent b45e143c84
commit 5e3d3c7c7d
139 changed files with 11420 additions and 747 deletions
--- a/docs/benchmarks/data/stemming-quality.csv
+++ b/docs/benchmarks/data/stemming-quality.csv
@@ -35,8 +35,8 @@ Stemmer,Language,Dictionary model ID,Dictionary model version,Dictionary model S
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@@ -205,24 +205,26 @@ Stemmer,Language,Dictionary model ID,Dictionary model version,Dictionary model S
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 "SNOWBALL_FRENCH_DIRECT","FR_FR","fr-fr-default","1.0.0","a988658758952fd599dc7360e0234178a6d65ac46e5cedc7dcd325a7cb7e71d9","ALL_WORDS","PRIMARY_OUTPUT","59240","404011","2301","404011","0","1","404011","85627","3744838","1092238","1625361","81605779618","1092238","81606871856","0.001338","1625361","5370199","30.266309","0.774194575401","0.697336914330","0.999986615858","0.999966701086","0.848661765094","0.757496924470","0.733758618240","0.711462917671","0.579477680015","0.734761496202","0.734744993787","0.000033298914","","","","",""
 "SNOWBALL_FRENCH_DIRECT","FR_FR","fr-fr-default","1.0.0","a988658758952fd599dc7360e0234178a6d65ac46e5cedc7dcd325a7cb7e71d9","LOWERCASE_GROUPS_ONLY","PRIMARY_OUTPUT","57698","400712","2133","400712","0","1","400712","84526","3736871","1088903","1619380","80278407962","1088903","80279496865","0.001356","1619380","5356251","30.233460","0.774356818202","0.697665400669","0.999986436101","0.999966266576","0.848825918385","0.757698693319","0.734013322497","0.711763857056","0.579795455624","0.735011537210","0.734994818860","0.000033733424","","","","",""
 "SNOWBALL_FRENCH_LUCENE_FILTER","FR_FR","fr-fr-default","1.0.0","a988658758952fd599dc7360e0234178a6d65ac46e5cedc7dcd325a7cb7e71d9","ALL_WORDS","PRIMARY_OUTPUT","59240","404011","2301","404011","0","1","404011","85202","3742072","1097843","1628127","81605774013","1097843","81606871856","0.001345","1628127","5370199","30.317815","0.773168950281","0.696821849619","0.999986547175","0.999966598516","0.848404198397","0.756589837411","0.733012775372","0.710860736247","0.578547882033","0.734003418250","0.733986862867","0.000033401484","","","","",""
 "SNOWBALL_FRENCH_LUCENE_FILTER","FR_FR","fr-fr-default","1.0.0","a988658758952fd599dc7360e0234178a6d65ac46e5cedc7dcd325a7cb7e71d9","LOWERCASE_GROUPS_ONLY","PRIMARY_OUTPUT","57698","400712","2133","400712","0","1","400712","84810","3734232","1086494","1622019","80278410371","1086494","80279496865","0.001353","1622019","5356251","30.282729","0.774620254294","0.697172705312","0.999986466109","0.999966263711","0.848579585710","0.757784104203","0.733858787339","0.711398006457","0.579602638316","0.734876927298","0.734860210439","0.000033736289","","","","",""
-"SNOWBALL_GERMAN_DIRECT","DE_DE","de-de-default","1.0.0","cbfa038122823f02e4bdb54b0035492c356b6ecd80f11eb11290d7a7248a59f5","ALL_WORDS","PRIMARY_OUTPUT","54092","277266","1474","277266","0","1","277266","81649","742376","65811","602476","38436668082","65811","38436733893","0.000171","602476","1344852","44.798684","0.918569588474","0.552013158325","0.999998287810","0.999982613933","0.776005723068","0.810879063265","0.689607573295","0.599890587538","0.526260347085","0.712083211201","0.712076031428","0.000017386067","","","","",""
-"SNOWBALL_GERMAN_DIRECT","DE_DE","de-de-default","1.0.0","cbfa038122823f02e4bdb54b0035492c356b6ecd80f11eb11290d7a7248a59f5","LOWERCASE_GROUPS_ONLY","PRIMARY_OUTPUT","16007","145574","228","145574","0","1","145574","37843","506459","41477","351958","10594922057","41477","10594963534","0.000391","351958","858417","41.000819","0.924303203294","0.589991810507","0.999996085215","0.999962868855","0.794993947861","0.830216831177","0.720244490537","0.635998708058","0.562798507380","0.738465517386","0.738449797528","0.000037131145","","","","",""
+"SNOWBALL_GERMAN_DIRECT","DE_DE","de-de-default","1.0.0","cbfa038122823f02e4bdb54b0035492c356b6ecd80f11eb11290d7a7248a59f5","ALL_WORDS","PRIMARY_OUTPUT","54092","277266","1474","277266","0","1","277266","81641","742393","65811","602459","38436668082","65811","38436733893","0.000171","602459","1344852","44.797420","0.918571301305","0.552025799121","0.999998287810","0.999982614376","0.776012043466","0.810885586285","0.689617919831","0.599902676509","0.526272398156","0.712092028219","0.712084848565","0.000017385624","","","","",""
+"SNOWBALL_GERMAN_DIRECT","DE_DE","de-de-default","1.0.0","cbfa038122823f02e4bdb54b0035492c356b6ecd80f11eb11290d7a7248a59f5","LOWERCASE_GROUPS_ONLY","PRIMARY_OUTPUT","16007","145574","228","145574","0","1","145574","37842","506464","41477","351953","10594922057","41477","10594963534","0.000391","351953","858417","41.000236","0.924303894032","0.589997635182","0.999996085215","0.999962869327","0.794996860199","0.830219583690","0.720249040429","0.636004188257","0.562804063590","0.738469438547","0.738453718829","0.000037130673","","","","",""
 "SNOWBALL_GERMAN_LUCENE_FILTER","DE_DE","de-de-default","1.0.0","cbfa038122823f02e4bdb54b0035492c356b6ecd80f11eb11290d7a7248a59f5","ALL_WORDS","PRIMARY_OUTPUT","54092","277266","1474","277266","0","1","277266","86669","723725","142783","621127","38436591110","142783","38436733893","0.000371","621127","1344852","46.185528","0.835220217240","0.538144717783","0.999996285246","0.999980126218","0.769070501515","0.752174652309","0.654551949931","0.579358576068","0.486493662760","0.670424751999","0.670415952491","0.000019873782","","","","",""
 "SNOWBALL_GERMAN_LUCENE_FILTER","DE_DE","de-de-default","1.0.0","cbfa038122823f02e4bdb54b0035492c356b6ecd80f11eb11290d7a7248a59f5","LOWERCASE_GROUPS_ONLY","PRIMARY_OUTPUT","16007","145574","228","145574","0","1","145574","46077","471644","34482","386773","10594929052","34482","10594963534","0.000325","386773","858417","45.056540","0.931870719939","0.549434598802","0.999996745435","0.999960243292","0.774715672118","0.817996747049","0.691284921032","0.598564290417","0.528216517210","0.715543160924","0.715527026594","0.000039756708","","","","",""
 "SNOWBALL_HUNGARIAN_DIRECT","HU_HU","hu-hu-default","1.0.0","359d46a01d751ec823705ad7f3dd1cc8f6663feb1a9d13cb04d0c6fb51ab646e","ALL_WORDS","PRIMARY_OUTPUT","19406","910688","1","910688","0","1","910688","116105","14275129","1281527","7842726","414652461946","1281527","414653743473","0.000309","7842726","22117855","35.458800","0.917621949087","0.645411998587","0.999996909404","0.999977996662","0.822704453996","0.846239680964","0.757813631609","0.686119053091","0.610064359819","0.769574048489","0.769564274829","0.000022003338","","","","",""
@@ -241,6 +243,10 @@ Stemmer,Language,Dictionary model ID,Dictionary model version,Dictionary model S
 "SNOWBALL_NORWEGIAN_NYNORSK_DIRECT","NN_NO","nn-no-default","1.0.0","900cf2005605aea2a3d8d731ec0b0c1f47fb4469b4ba6b9134145d4d026a0398","LOWERCASE_GROUPS_ONLY","PRIMARY_OUTPUT","4681","16906","23","16906","0","1","16906","6120","20847","1201","7458","142868459","1201","142869660","0.000841","7458","28305","26.348702","0.945527939042","0.736512983572","0.999991593737","0.999939404316","0.868252288654","0.894744070663","0.828034079399","0.770581364403","0.706534264217","0.834502009245","0.834474211808","0.000060595684","","","","",""
 "SNOWBALL_NORWEGIAN_NYNORSK_LUCENE_FILTER","NN_NO","nn-no-default","1.0.0","900cf2005605aea2a3d8d731ec0b0c1f47fb4469b4ba6b9134145d4d026a0398","ALL_WORDS","PRIMARY_OUTPUT","4688","16937","23","16937","0","1","16937","6144","20854","1222","7508","143392932","1222","143394154","0.000852","7508","28362","26.472040","0.944645769161","0.735279599464","0.999991478035","0.999939130896","0.867635538749","0.893747964274","0.826916213966","0.769384020542","0.704908058410","0.833413920441","0.833385994629","0.000060869104","","","","",""
 "SNOWBALL_NORWEGIAN_NYNORSK_LUCENE_FILTER","NN_NO","nn-no-default","1.0.0","900cf2005605aea2a3d8d731ec0b0c1f47fb4469b4ba6b9134145d4d026a0398","LOWERCASE_GROUPS_ONLY","PRIMARY_OUTPUT","4681","16906","23","16906","0","1","16906","6130","20824","1201","7481","142868459","1201","142869660","0.000841","7481","28305","26.429959","0.945471055619","0.735700406289","0.999991593737","0.999939243362","0.867846000013","0.894463296250","0.827498509835","0.769862102111","0.705754761743","0.834016450529","0.833988591624","0.000060756638","","","","",""
+"SNOWBALL_PERSIAN_DIRECT","FA_IR","fa-ir-default","1.0.0","b29a0d168a6a97f980666aa40b74a0edd8b6be4ab3320a7abfbb76b3529f4ea1","ALL_WORDS","PRIMARY_OUTPUT","69","3544","0","3544","0","1","3544","2029","6748","79","89296","6182073","79","6182152","0.001278","89296","96044","92.974054","0.988428299399","0.070259464412","0.999987221278","0.985764222716","0.535123342845","0.273526169012","0.131193436440","0.086290898024","0.070201720712","0.263526930171","0.261598150185","0.014235777284","","","","",""
+"SNOWBALL_PERSIAN_DIRECT","FA_IR","fa-ir-default","1.0.0","b29a0d168a6a97f980666aa40b74a0edd8b6be4ab3320a7abfbb76b3529f4ea1","LOWERCASE_GROUPS_ONLY","PRIMARY_OUTPUT","69","3544","0","3544","0","1","3544","2029","6748","79","89296","6182073","79","6182152","0.001278","89296","96044","92.974054","0.988428299399","0.070259464412","0.999987221278","0.985764222716","0.535123342845","0.273526169012","0.131193436440","0.086290898024","0.070201720712","0.263526930171","0.261598150185","0.014235777284","","","","",""
+"SNOWBALL_POLISH_DIRECT","PL_PL","pl-pl-unimorph","1.0.0","8191ed727097839cc808cbc5c56a1bd78b3c851e7733ad226ad9a51519a54721","ALL_WORDS","PRIMARY_OUTPUT","9990","120867","1","120867","0","1","120867","19265","723037","70656","394036","7303167682","70656","7303238338","0.000967","394036","1117073","35.273970","0.910978174181","0.647260295433","0.999990325388","0.999936381518","0.823625310410","0.842338201869","0.756803292502","0.687038256475","0.608755869394","0.767880200391","0.767851723211","0.000063618482","","","","",""
+"SNOWBALL_POLISH_DIRECT","PL_PL","pl-pl-unimorph","1.0.0","8191ed727097839cc808cbc5c56a1bd78b3c851e7733ad226ad9a51519a54721","LOWERCASE_GROUPS_ONLY","PRIMARY_OUTPUT","9846","119451","1","119451","0","1","119451","18927","718592","70647","392165","7133029571","70647","7133100218","0.000990","392165","1110757","35.306102","0.910487190826","0.646938979453","0.999990095891","0.999935127795","0.823464537672","0.841893538764","0.756414224030","0.686692785364","0.608252553741","0.767482673444","0.767453627968","0.000064872205","","","","",""
 "SNOWBALL_PORTUGUESE_DIRECT","PT_PT","pt-pt-default","1.0.0","7a035ff330a6f0548f446cd0d6617bc1cf4751292125a3564d3a255c5d6f516d","ALL_WORDS","PRIMARY_OUTPUT","4001","211091","0","211091","0","1","211091","11315","4816198","146201","670154","22273967042","146201","22274113243","0.000656","670154","5486352","12.214929","0.970538241685","0.877850710272","0.999993436282","0.999963358632","0.938922073277","0.950467296507","0.921870566157","0.894944355740","0.855064834721","0.923031789707","0.923014032222","0.000036641368","","","","",""
 "SNOWBALL_PORTUGUESE_DIRECT","PT_PT","pt-pt-default","1.0.0","7a035ff330a6f0548f446cd0d6617bc1cf4751292125a3564d3a255c5d6f516d","LOWERCASE_GROUPS_ONLY","PRIMARY_OUTPUT","4001","211091","0","211091","0","1","211091","11315","4816198","146201","670154","22273967042","146201","22274113243","0.000656","670154","5486352","12.214929","0.970538241685","0.877850710272","0.999993436282","0.999963358632","0.938922073277","0.950467296507","0.921870566157","0.894944355740","0.855064834721","0.923031789707","0.923014032222","0.000036641368","","","","",""
 "SNOWBALL_PORTUGUESE_LUCENE_FILTER","PT_PT","pt-pt-default","1.0.0","7a035ff330a6f0548f446cd0d6617bc1cf4751292125a3564d3a255c5d6f516d","ALL_WORDS","PRIMARY_OUTPUT","4001","211091","0","211091","0","1","211091","11315","4816198","146201","670154","22273967042","146201","22274113243","0.000656","670154","5486352","12.214929","0.970538241685","0.877850710272","0.999993436282","0.999963358632","0.938922073277","0.950467296507","0.921870566157","0.894944355740","0.855064834721","0.923031789707","0.923014032222","0.000036641368","","","","",""
--- a/docs/benchmarks/data/stemming-quality.sha256
+++ b/docs/benchmarks/data/stemming-quality.sha256
@@ -1 +1 @@
-edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8  stemming-quality.csv
+d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5  stemming-quality.csv
--- a/docs/benchmarks/index.md
+++ b/docs/benchmarks/index.md
@@ -52,8 +52,8 @@ Open [Language Benchmark Pages](languages/index.md) for the complete language li

 The English dictionary coverage benchmark shows the current contracted-trie operating curve. With
 the full English dictionary, Radixor reaches `97.478%` all-token exactness and `97.197%`
-changed-token exactness at `98.0 ns/token`. Even with a deterministic 10% dictionary slice, it
-keeps `92.868%` all-token exactness and `76.516%` changed-token exactness at `80.6 ns/token`.
+changed-token exactness at `71.6 ns/token`. Even with a deterministic 10% dictionary slice, it
+keeps `92.868%` all-token exactness and `76.516%` changed-token exactness at `47.0 ns/token`.

 Those figures should not be reduced to a single speed badge. The professional interpretation is a
 quality/speed envelope: the amount and quality of dictionary knowledge affect stemming precision,
@@ -61,7 +61,17 @@ while contracted tries reduce lookup cost in uniform regions of the compiled gra

 ## Quality versus performance

-Each language page keeps exact-root accuracy, JMH latency, and pairwise linguistic-quality results in separate tables. No undocumented scalar combines them. The 2026-07-23 language tables are generated from the unrounded JMH comparison report produced on the environment documented for this refresh. Readers should inspect the quality and speed dimensions side by side; no cross-language Pareto ranking is inferred from workloads with different dictionaries and token counts.
+Each language page keeps exact-root accuracy, JMH latency, and pairwise linguistic-quality results in separate tables. No undocumented scalar combines them. The 2026-08-10 language tables are generated exclusively from the current unrounded JMH comparison report produced on the environment documented for this refresh. The Snowball 3.1.0 matrix adds direct Czech, Persian, and Polish stemmers; all previously published Java stemmers were measured again in the same run. Readers should inspect the quality and speed dimensions side by side; no cross-language Pareto ranking is inferred from workloads with different dictionaries and token counts.
+
+### New Snowball 3.1.0 rows
+
+| New direct stemmer | All exact | Changed exact | Root preserved | Speed | Relative to same-language Radixor |
+| --- | ---: | ---: | ---: | ---: | ---: |
+| Czech | 19.865% | 18.186% | 27.645% | 82.4 ns/token | 1.187× |
+| Persian | 3.660% | 0.000% | 100.000% | 298.1 ns/token | 6.486× |
+| Polish | 22.315% | 20.225% | 34.078% | 86.5 ns/token | 1.196× |
+
+These rows describe exact agreement with each Radixor model dictionary and the measured direct API workload; they are not a universal linguistic ranking. In this dataset the three new Snowball stemmers are both less exact and slower than their same-language Radixor baseline. Lucene 10.5.0 does not expose the three new algorithms through `SnowballFilter`, so no synthetic Lucene wrapper rows were added.

 <!-- STEMMING-QUALITY-OVERVIEW:START -->

@@ -76,16 +86,16 @@ The validated snapshot is a broad multilingual comparison covering the complete

 | Language | Dictionary mode | Winner | Balanced accuracy | Runner-up | Difference | Exact tie | Deterministic stemmers |
 |---|---|---|---:|---|---:|---|---:|
-|Czech (`CS_CZ`)|ALL_WORDS|Radixor|0.996617|HUNSPELL CZECH LUCENE FILTER|0.142485045|no|3|
-|Czech (`CS_CZ`)|LOWERCASE_GROUPS_ONLY|Radixor|0.997195|HUNSPELL CZECH LUCENE FILTER|0.144045088|no|3|
-|Danish (`DA_DK`)|ALL_WORDS|Radixor|0.996243|SNOWBALL DANISH LUCENE FILTER|0.058337376|no|3|
-|Danish (`DA_DK`)|LOWERCASE_GROUPS_ONLY|Radixor|0.996482|SNOWBALL DANISH DIRECT|0.058471663|no|3|
+|Czech (`CS_CZ`)|ALL_WORDS|Radixor|0.996617|HUNSPELL CZECH LUCENE FILTER|0.142485045|no|4|
+|Czech (`CS_CZ`)|LOWERCASE_GROUPS_ONLY|Radixor|0.997195|HUNSPELL CZECH LUCENE FILTER|0.144045088|no|4|
+|Danish (`DA_DK`)|ALL_WORDS|Radixor|0.996243|SNOWBALL DANISH DIRECT|0.053760569|no|3|
+|Danish (`DA_DK`)|LOWERCASE_GROUPS_ONLY|Radixor|0.996482|SNOWBALL DANISH DIRECT|0.054099342|no|3|
 |Dutch (`NL_NL`)|ALL_WORDS|Radixor|0.988733|SNOWBALL DUTCH DIRECT|0.261639748|no|4|
 |Dutch (`NL_NL`)|LOWERCASE_GROUPS_ONLY|Radixor|0.989114|SNOWBALL DUTCH DIRECT|0.258605347|no|4|
 |English (`US_UK`)|ALL_WORDS|Radixor|0.965537|ENGLISH LUCENE PORTER COPIED|0.010741250|no|11|
 |English (`US_UK`)|LOWERCASE_GROUPS_ONLY|Radixor|0.966202|ENGLISH LUCENE PORTER COPIED|0.011138557|no|11|
 |Finnish (`FI_FI`)|ALL_WORDS|Radixor|0.984838|SNOWBALL FINNISH LUCENE FILTER|0.244558928|no|4|
-|Finnish (`FI_FI`)|LOWERCASE_GROUPS_ONLY|Radixor|0.988242|SNOWBALL FINNISH DIRECT|0.249897933|no|4|
+|Finnish (`FI_FI`)|LOWERCASE_GROUPS_ONLY|Radixor|0.988242|SNOWBALL FINNISH DIRECT|0.249699076|no|4|
 |French (`FR_FR`)|ALL_WORDS|Radixor|0.958627|SNOWBALL FRENCH DIRECT|0.109964908|no|6|
 |French (`FR_FR`)|LOWERCASE_GROUPS_ONLY|Radixor|0.958856|SNOWBALL FRENCH DIRECT|0.110030565|no|6|
 |German (`DE_DE`)|ALL_WORDS|Radixor|0.910445|GERMAN CISTEM|0.031918024|no|8|
@@ -100,10 +110,10 @@ The validated snapshot is a broad multilingual comparison covering the complete
 |Norwegian Bokmal (`NB_NO`)|LOWERCASE_GROUPS_ONLY|Radixor|0.976240|SNOWBALL NORWEGIAN BOKMAL DIRECT|0.101954266|no|5|
 |Norwegian Nynorsk (`NN_NO`)|ALL_WORDS|Radixor|0.950991|SNOWBALL NORWEGIAN NYNORSK DIRECT|0.082896791|no|3|
 |Norwegian Nynorsk (`NN_NO`)|LOWERCASE_GROUPS_ONLY|Radixor|0.951104|SNOWBALL NORWEGIAN NYNORSK DIRECT|0.082851757|no|3|
-|Persian (`FA_IR`)|ALL_WORDS|Radixor|0.976360|PERSIAN LUCENE PERSIAN STEM FILTER|0.474147508|no|2|
-|Persian (`FA_IR`)|LOWERCASE_GROUPS_ONLY|Radixor|0.976360|PERSIAN LUCENE PERSIAN STEM FILTER|0.474147508|no|2|
-|Polish (`PL_PL`)|ALL_WORDS|Radixor|0.991105|POLISH LUCENE MORFOLOGIK FILTER|0.042712804|no|5|
-|Polish (`PL_PL`)|LOWERCASE_GROUPS_ONLY|Radixor|0.991301|POLISH LUCENE MORFOLOGIK FILTER|0.042883749|no|5|
+|Persian (`FA_IR`)|ALL_WORDS|Radixor|0.976360|SNOWBALL PERSIAN DIRECT|0.441236451|no|3|
+|Persian (`FA_IR`)|LOWERCASE_GROUPS_ONLY|Radixor|0.976360|SNOWBALL PERSIAN DIRECT|0.441236451|no|3|
+|Polish (`PL_PL`)|ALL_WORDS|Radixor|0.991105|POLISH LUCENE MORFOLOGIK FILTER|0.042712804|no|6|
+|Polish (`PL_PL`)|LOWERCASE_GROUPS_ONLY|Radixor|0.991301|POLISH LUCENE MORFOLOGIK FILTER|0.042883749|no|6|
 |Portuguese (`PT_PT`)|ALL_WORDS|Radixor|0.998542|SNOWBALL PORTUGUESE DIRECT|0.059619854|no|6|
 |Portuguese (`PT_PT`)|LOWERCASE_GROUPS_ONLY|Radixor|0.998542|SNOWBALL PORTUGUESE DIRECT|0.059619854|no|6|
 |Russian (`RU_RU`)|ALL_WORDS|Radixor|0.990188|SNOWBALL RUSSIAN LUCENE FILTER|0.155623602|no|4|
@@ -166,7 +176,7 @@ Counts use `PRIMARY_OUTPUT` only and retain each adapter configuration as a sepa
 |ITALIAN LUCENE ITALIAN LIGHT STEM FILTER|1|0|0|0|4.000|4.000|
 |NORWEGIAN BOKMAL LUCENE NORWEGIAN LIGHT STEM FILTER|1|0|0|0|4.000|4.000|
 |NORWEGIAN BOKMAL LUCENE NORWEGIAN MINIMAL STEM FILTER|1|0|0|0|5.000|5.000|
-|PERSIAN LUCENE PERSIAN STEM FILTER|1|0|0|1|2.000|2.000|
+|PERSIAN LUCENE PERSIAN STEM FILTER|1|0|0|1|3.000|3.000|
 |POLISH LUCENE MORFOLOGIK FILTER|1|0|0|1|2.000|2.000|
 |POLISH LUCENE STEMPEL DIRECT|1|0|0|0|4.000|4.000|
 |POLISH LUCENE STEMPEL FILTER|1|0|0|0|5.000|5.000|
@@ -174,8 +184,9 @@ Counts use `PRIMARY_OUTPUT` only and retain each adapter configuration as a sepa
 |PORTUGUESE LUCENE PORTUGUESE MINIMAL STEM FILTER|1|0|0|0|6.000|6.000|
 |PORTUGUESE LUCENE PORTUGUESE STEM FILTER|1|0|0|0|4.000|4.000|
 |RUSSIAN LUCENE RUSSIAN LIGHT STEM FILTER|1|0|0|0|4.000|4.000|
-|SNOWBALL DANISH DIRECT|1|0|0|1|3.000|3.000|
-|SNOWBALL DANISH LUCENE FILTER|1|0|0|1|2.000|2.000|
+|SNOWBALL CZECH DIRECT|1|0|0|0|4.000|4.000|
+|SNOWBALL DANISH DIRECT|1|0|0|1|2.000|2.000|
+|SNOWBALL DANISH LUCENE FILTER|1|0|0|1|3.000|3.000|
 |SNOWBALL DUTCH DIRECT|1|0|0|1|2.000|2.000|
 |SNOWBALL DUTCH LUCENE FILTER|1|0|0|0|4.000|4.000|
 |SNOWBALL FINNISH DIRECT|1|0|0|1|3.000|3.000|
@@ -192,6 +203,8 @@ Counts use `PRIMARY_OUTPUT` only and retain each adapter configuration as a sepa
 |SNOWBALL NORWEGIAN BOKMAL LUCENE FILTER|1|0|0|1|3.000|3.000|
 |SNOWBALL NORWEGIAN NYNORSK DIRECT|1|0|0|1|2.000|2.000|
 |SNOWBALL NORWEGIAN NYNORSK LUCENE FILTER|1|0|0|1|3.000|3.000|
+|SNOWBALL PERSIAN DIRECT|1|0|0|1|2.000|2.000|
+|SNOWBALL POLISH DIRECT|1|0|0|0|6.000|6.000|
 |SNOWBALL PORTUGUESE DIRECT|1|0|0|1|2.000|2.000|
 |SNOWBALL PORTUGUESE LUCENE FILTER|1|0|0|1|3.000|3.000|
 |SNOWBALL RUSSIAN DIRECT|1|0|0|1|3.000|3.000|
@@ -246,7 +259,7 @@ Counts use `PRIMARY_OUTPUT` only and retain each adapter configuration as a sepa
 |ITALIAN LUCENE ITALIAN LIGHT STEM FILTER|1|0|0|0|4.000|4.000|
 |NORWEGIAN BOKMAL LUCENE NORWEGIAN LIGHT STEM FILTER|1|0|0|0|4.000|4.000|
 |NORWEGIAN BOKMAL LUCENE NORWEGIAN MINIMAL STEM FILTER|1|0|0|0|5.000|5.000|
-|PERSIAN LUCENE PERSIAN STEM FILTER|1|0|0|1|2.000|2.000|
+|PERSIAN LUCENE PERSIAN STEM FILTER|1|0|0|1|3.000|3.000|
 |POLISH LUCENE MORFOLOGIK FILTER|1|0|0|1|2.000|2.000|
 |POLISH LUCENE STEMPEL DIRECT|1|0|0|0|4.000|4.000|
 |POLISH LUCENE STEMPEL FILTER|1|0|0|0|5.000|5.000|
@@ -254,6 +267,7 @@ Counts use `PRIMARY_OUTPUT` only and retain each adapter configuration as a sepa
 |PORTUGUESE LUCENE PORTUGUESE MINIMAL STEM FILTER|1|0|0|0|6.000|6.000|
 |PORTUGUESE LUCENE PORTUGUESE STEM FILTER|1|0|0|0|4.000|4.000|
 |RUSSIAN LUCENE RUSSIAN LIGHT STEM FILTER|1|0|0|0|4.000|4.000|
+|SNOWBALL CZECH DIRECT|1|0|0|0|4.000|4.000|
 |SNOWBALL DANISH DIRECT|1|0|0|1|2.000|2.000|
 |SNOWBALL DANISH LUCENE FILTER|1|0|0|1|3.000|3.000|
 |SNOWBALL DUTCH DIRECT|1|0|0|1|2.000|2.000|
@@ -272,6 +286,8 @@ Counts use `PRIMARY_OUTPUT` only and retain each adapter configuration as a sepa
 |SNOWBALL NORWEGIAN BOKMAL LUCENE FILTER|1|0|0|1|3.000|3.000|
 |SNOWBALL NORWEGIAN NYNORSK DIRECT|1|0|0|1|2.000|2.000|
 |SNOWBALL NORWEGIAN NYNORSK LUCENE FILTER|1|0|0|1|3.000|3.000|
+|SNOWBALL PERSIAN DIRECT|1|0|0|1|2.000|2.000|
+|SNOWBALL POLISH DIRECT|1|0|0|0|6.000|6.000|
 |SNOWBALL PORTUGUESE DIRECT|1|0|0|1|2.000|2.000|
 |SNOWBALL PORTUGUESE LUCENE FILTER|1|0|0|1|3.000|3.000|
 |SNOWBALL RUSSIAN DIRECT|1|0|0|1|2.000|2.000|
@@ -305,7 +321,7 @@ These aggregates cover all 20 documented languages. Macro balanced accuracy give
 ### Reproducible data

 - [Machine-readable quality snapshot](data/stemming-quality.csv)
- SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - [Linguistic quality methodology](reference/linguistic-quality.md)
 - [Tested stemmer inventory](reference/tested-stemmers.md)
 - [Reproducibility and raw data](reference/reproducibility.md)
--- a/docs/benchmarks/languages/czech.md
+++ b/docs/benchmarks/languages/czech.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `cs-cz-default` | `1.0.0` | `CS_CZ` | 5,113 | 56,612 | 10,049 | 46,563 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `cs-cz-default` | `1.0.0` | `CS_CZ` | 5,113 | 56,612 | 10,049 | 46,563 | 46,563 |

 ## Radixor Patch Command Distribution

@@ -30,14 +30,10 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 99.465% | 99.439% | 99.582% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 99.465% | 99.439% | 99.582% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene HunspellStemFilter | 84.850% | 82.269% | 96.806% | Benchmark-only Czech Hunspell dictionary compared via Lucene HunspellStemFilter. |
 | Lucene CzechStemFilter | 16.784% | 15.538% | 22.559% | Lucene Czech suffix stemmer implemented as a TokenFilter. |
-
-
-
-
-
+| Official Snowball direct | 19.865% | 18.186% | 27.645% | Official Snowball 3.1.0 generated Java stemmer; rule-based suffix algorithm. |

 ## Speed

@@ -45,18 +41,14 @@ Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 i

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `czechRadixor` | 3.395 | 0.066 | 72.9 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 381.189 | 32.563 | 8186.5 | 112.265 | Benchmark-only Czech Hunspell dictionary compared via Lucene HunspellStemFilter. |
-| Lucene CzechStemFilter | `czechLuceneCzechStemFilter` | 3.125 | 0.042 | 67.1 | 0.920 | Czech suffix stemmer implemented as a Lucene TokenFilter. |
-
-
-
-
-
+| Radixor | `czechRadixor` | 3.230 | 0.050 | 69.4 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 349.111 | 24.459 | 7497.6 | 108.091 | Benchmark-only Czech Hunspell dictionary compared via Lucene HunspellStemFilter. |
+| Lucene CzechStemFilter | `czechLuceneCzechStemFilter` | 2.927 | 0.032 | 62.9 | 0.906 | Czech suffix stemmer implemented as a Lucene TokenFilter. |
+| Official Snowball direct | `snowballDirect[CZECH]` | 3.835 | 0.320 | 82.4 | 1.187 | Official Snowball 3.1.0 generated Java stemmer; direct API. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -74,11 +66,11 @@ Runtime performance and linguistic grouping quality are independent dimensions.

 The default model is `cs-cz-default`, loaded from classpath resource `org/egothor/stemmer/models/cs-cz-default/stemmer.gz`. The following findings compare only deterministic `PRIMARY_OUTPUT` rows over identical included groups; candidate policies are reported separately as capability analyses.

- **ALL_WORDS:** `Radixor` ranks first by balanced accuracy at **0.996617** among 3 deterministic stemmers. The runner-up is `HUNSPELL CZECH LUCENE FILTER` at 0.854132, a difference of 0.142485. This rank does not imply leadership in throughput or every secondary metric.
- **LOWERCASE_GROUPS_ONLY:** `Radixor` ranks first by balanced accuracy at **0.997195** among 3 deterministic stemmers. The runner-up is `HUNSPELL CZECH LUCENE FILTER` at 0.853150, a difference of 0.144045. This rank does not imply leadership in throughput or every secondary metric.
+- **ALL_WORDS:** `Radixor` ranks first by balanced accuracy at **0.996617** among 4 deterministic stemmers. The runner-up is `HUNSPELL CZECH LUCENE FILTER` at 0.854132, a difference of 0.142485. This rank does not imply leadership in throughput or every secondary metric.
+- **LOWERCASE_GROUPS_ONLY:** `Radixor` ranks first by balanced accuracy at **0.997195** among 4 deterministic stemmers. The runner-up is `HUNSPELL CZECH LUCENE FILTER` at 0.853150, a difference of 0.144045. This rank does not imply leadership in throughput or every secondary metric.
 ### `ALL_WORDS`

-This mode contains **7 result rows**, **3 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.
+This mode contains **8 result rows**, **4 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.

 #### `PRIMARY_OUTPUT` ranking

@@ -89,6 +81,7 @@ This mode contains **7 result rows**, **3 evaluated stemmers**, and **3 output p
 |1|Radixor|0.996617|0.000000%|0.676519%|
 |2|HUNSPELL CZECH LUCENE FILTER|0.854132|0.000691%|29.172837%|
 |3|CZECH LUCENE CZECH STEM FILTER|0.794343|0.000928%|41.130549%|
+|4|SNOWBALL CZECH DIRECT|0.786366|0.000904%|42.725842%|

 </div>

@@ -99,6 +92,7 @@ This mode contains **7 result rows**, **3 evaluated stemmers**, and **3 output p
 |1|Radixor|PRIMARY_OUTPUT|1.000000|0.993235|1.000000|0.996617|0.999998|0.000002|
 |2|HUNSPELL CZECH LUCENE FILTER|PRIMARY_OUTPUT|0.958877|0.708272|0.999993|0.854132|0.999927|0.000073|
 |3|CZECH LUCENE CZECH STEM FILTER|PRIMARY_OUTPUT|0.935210|0.588695|0.999991|0.794343|0.999897|0.000103|
+|4|SNOWBALL CZECH DIRECT|PRIMARY_OUTPUT|0.935153|0.572742|0.999991|0.786366|0.999894|0.000106|

 </details>

@@ -109,6 +103,7 @@ This mode contains **7 result rows**, **3 evaluated stemmers**, and **3 output p
 |1|Radixor|PRIMARY_OUTPUT|0.998640|0.996606|0.994581|0.993235|0.996612|0.996611|
 |2|HUNSPELL CZECH LUCENE FILTER|PRIMARY_OUTPUT|0.895506|0.814739|0.747335|0.687392|0.824103|0.824070|
 |3|CZECH LUCENE CZECH STEM FILTER|PRIMARY_OUTPUT|0.836710|0.722556|0.635811|0.565626|0.741992|0.741949|
+|4|SNOWBALL CZECH DIRECT|PRIMARY_OUTPUT|0.830101|0.710396|0.620864|0.550864|0.731848|0.731804|

 </details>

@@ -119,6 +114,7 @@ This mode contains **7 result rows**, **3 evaluated stemmers**, and **3 output p
 |1|Radixor|PRIMARY_OUTPUT|298476|0|2033|1320705191|0 / 1320705191|2033 / 300509|
 |2|HUNSPELL CZECH LUCENE FILTER|PRIMARY_OUTPUT|212842|9128|87667|1320696063|9128 / 1320705191|87667 / 300509|
 |3|CZECH LUCENE CZECH STEM FILTER|PRIMARY_OUTPUT|176908|12256|123601|1320692935|12256 / 1320705191|123601 / 300509|
+|4|SNOWBALL CZECH DIRECT|PRIMARY_OUTPUT|172114|11935|128395|1320693256|11935 / 1320705191|128395 / 300509|

 </details>

@@ -193,7 +189,7 @@ Alternative candidates are capability analyses, not replacements for the determi

 ### `LOWERCASE_GROUPS_ONLY`

-This mode contains **7 result rows**, **3 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.
+This mode contains **8 result rows**, **4 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.

 #### `PRIMARY_OUTPUT` ranking

@@ -204,6 +200,7 @@ This mode contains **7 result rows**, **3 evaluated stemmers**, and **3 output p
 |1|Radixor|0.997195|0.000000%|0.561033%|
 |2|HUNSPELL CZECH LUCENE FILTER|0.853150|0.000700%|29.369351%|
 |3|CZECH LUCENE CZECH STEM FILTER|0.792522|0.000918%|41.494586%|
+|4|SNOWBALL CZECH DIRECT|0.784821|0.000923%|43.034822%|

 </div>

@@ -214,6 +211,7 @@ This mode contains **7 result rows**, **3 evaluated stemmers**, and **3 output p
 |1|Radixor|PRIMARY_OUTPUT|1.000000|0.994390|1.000000|0.997195|0.999999|0.000001|
 |2|HUNSPELL CZECH LUCENE FILTER|PRIMARY_OUTPUT|0.958957|0.706306|0.999993|0.853150|0.999925|0.000075|
 |3|CZECH LUCENE CZECH STEM FILTER|PRIMARY_OUTPUT|0.936557|0.585054|0.999991|0.792522|0.999895|0.000105|
+|4|SNOWBALL CZECH DIRECT|PRIMARY_OUTPUT|0.934577|0.569652|0.999991|0.784821|0.999891|0.000109|

 </details>

@@ -224,6 +222,7 @@ This mode contains **7 result rows**, **3 evaluated stemmers**, and **3 output p
 |1|Radixor|PRIMARY_OUTPUT|0.998873|0.997187|0.995507|0.994390|0.997191|0.997190|
 |2|HUNSPELL CZECH LUCENE FILTER|PRIMARY_OUTPUT|0.894932|0.813466|0.745594|0.685581|0.822993|0.822960|
 |3|CZECH LUCENE CZECH STEM FILTER|PRIMARY_OUTPUT|0.836092|0.720206|0.632534|0.562751|0.740227|0.740184|
+|4|SNOWBALL CZECH DIRECT|PRIMARY_OUTPUT|0.828436|0.707849|0.617907|0.547807|0.729646|0.729601|

 </details>

@@ -234,6 +233,7 @@ This mode contains **7 result rows**, **3 evaluated stemmers**, and **3 output p
 |1|Radixor|PRIMARY_OUTPUT|295818|0|1669|1284770069|0 / 1284770069|1669 / 297487|
 |2|HUNSPELL CZECH LUCENE FILTER|PRIMARY_OUTPUT|210117|8993|87370|1284761076|8993 / 1284770069|87370 / 297487|
 |3|CZECH LUCENE CZECH STEM FILTER|PRIMARY_OUTPUT|174046|11790|123441|1284758279|11790 / 1284770069|123441 / 297487|
+|4|SNOWBALL CZECH DIRECT|PRIMARY_OUTPUT|169464|11863|128023|1284758206|11863 / 1284770069|128023 / 297487|

 </details>

@@ -330,7 +330,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `CS_CZ`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/danish.md
+++ b/docs/benchmarks/languages/danish.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `da-dk-default` | `1.0.0` | `DA_DK` | 4,179 | 32,256 | 8,356 | 23,900 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `da-dk-default` | `1.0.0` | `DA_DK` | 4,179 | 32,256 | 8,356 | 23,900 | 23,900 |

 ## Radixor Patch Command Distribution

@@ -30,14 +30,9 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 99.371% | 99.527% | 98.923% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 99.371% | 99.527% | 98.923% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene SnowballFilter | 55.509% | 54.159% | 59.371% | Lucene TokenFilter integration path around the Snowball algorithm. |
-| Official Snowball direct | 55.509% | 54.159% | 59.371% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
-
-
-
-
-
+| Official Snowball direct | 55.971% | 54.791% | 59.347% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |

 ## Speed

@@ -45,18 +40,13 @@ Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 i

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `radixor[DANISH]` | 1.206 | 0.134 | 50.5 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Official Snowball direct | `snowballDirect[DANISH]` | 2.326 | 0.205 | 97.3 | 1.928 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[DANISH]` | 3.275 | 0.335 | 137.0 | 2.716 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-
-
-
-
-
+| Radixor | `radixor[DANISH]` | 1.146 | 0.122 | 47.9 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Official Snowball direct | `snowballDirect[DANISH]` | 2.542 | 0.179 | 106.4 | 2.219 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[DANISH]` | 2.879 | 0.239 | 120.4 | 2.512 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -74,8 +64,8 @@ Runtime performance and linguistic grouping quality are independent dimensions.

 The default model is `da-dk-default`, loaded from classpath resource `org/egothor/stemmer/models/da-dk-default/stemmer.gz`. The following findings compare only deterministic `PRIMARY_OUTPUT` rows over identical included groups; candidate policies are reported separately as capability analyses.

- **ALL_WORDS:** `Radixor` ranks first by balanced accuracy at **0.996243** among 3 deterministic stemmers. The runner-up is `SNOWBALL DANISH LUCENE FILTER` at 0.937905, a difference of 0.058337. This rank does not imply leadership in throughput or every secondary metric.
- **LOWERCASE_GROUPS_ONLY:** `Radixor` ranks first by balanced accuracy at **0.996482** among 3 deterministic stemmers. The runner-up is `SNOWBALL DANISH DIRECT` at 0.938010, a difference of 0.058472. This rank does not imply leadership in throughput or every secondary metric.
+- **ALL_WORDS:** `Radixor` ranks first by balanced accuracy at **0.996243** among 3 deterministic stemmers. The runner-up is `SNOWBALL DANISH DIRECT` at 0.942482, a difference of 0.053761. This rank does not imply leadership in throughput or every secondary metric.
+- **LOWERCASE_GROUPS_ONLY:** `Radixor` ranks first by balanced accuracy at **0.996482** among 3 deterministic stemmers. The runner-up is `SNOWBALL DANISH DIRECT` at 0.942383, a difference of 0.054099. This rank does not imply leadership in throughput or every secondary metric.
 ### `ALL_WORDS`

 This mode contains **5 result rows**, **3 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.
@@ -87,8 +77,8 @@ This mode contains **5 result rows**, **3 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Balanced accuracy | Over-stemming (OI) | Under-stemming (UI) |
 |---:|---|---:|---:|---:|
 |1|Radixor|0.996243|0.000000%|0.751435%|
-|2|SNOWBALL DANISH LUCENE FILTER|0.937905|0.001273%|12.417638%|
-|3|SNOWBALL DANISH DIRECT|0.937839|0.001230%|12.431016%|
+|2|SNOWBALL DANISH DIRECT|0.942482|0.001236%|11.502313%|
+|3|SNOWBALL DANISH LUCENE FILTER|0.937905|0.001273%|12.417638%|

 </div>

@@ -97,8 +87,8 @@ This mode contains **5 result rows**, **3 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | Precision | Recall | Specificity | Balanced accuracy | Pairwise accuracy | Error rate |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|1.000000|0.992486|1.000000|0.996243|0.999998|0.000002|
-|2|SNOWBALL DANISH LUCENE FILTER|PRIMARY_OUTPUT|0.940600|0.875824|0.999987|0.937905|0.999959|0.000041|
-|3|SNOWBALL DANISH DIRECT|PRIMARY_OUTPUT|0.942465|0.875690|0.999988|0.937839|0.999959|0.000041|
+|2|SNOWBALL DANISH DIRECT|PRIMARY_OUTPUT|0.942799|0.884977|0.999988|0.942482|0.999961|0.000039|
+|3|SNOWBALL DANISH LUCENE FILTER|PRIMARY_OUTPUT|0.940600|0.875824|0.999987|0.937905|0.999959|0.000041|

 </details>

@@ -107,8 +97,8 @@ This mode contains **5 result rows**, **3 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | F0.5 | F1 | F2 | Jaccard | Fowlkes–Mallows | MCC |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|0.998488|0.996229|0.993979|0.992486|0.996236|0.996235|
-|2|SNOWBALL DANISH LUCENE FILTER|PRIMARY_OUTPUT|0.926889|0.907057|0.888055|0.829921|0.907634|0.907614|
-|3|SNOWBALL DANISH DIRECT|PRIMARY_OUTPUT|0.928307|0.907851|0.888277|0.831252|0.908464|0.908444|
+|2|SNOWBALL DANISH DIRECT|PRIMARY_OUTPUT|0.930638|0.912973|0.895967|0.839881|0.913430|0.913411|
+|3|SNOWBALL DANISH LUCENE FILTER|PRIMARY_OUTPUT|0.926889|0.907057|0.888055|0.829921|0.907634|0.907614|

 </details>

@@ -117,8 +107,8 @@ This mode contains **5 result rows**, **3 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | TP | FP | FN | TN | Over error / possible | Under error / possible |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|89021|0|674|389687465|0 / 389687465|674 / 89695|
-|2|SNOWBALL DANISH LUCENE FILTER|PRIMARY_OUTPUT|78557|4961|11138|389682504|4961 / 389687465|11138 / 89695|
-|3|SNOWBALL DANISH DIRECT|PRIMARY_OUTPUT|78545|4795|11150|389682670|4795 / 389687465|11150 / 89695|
+|2|SNOWBALL DANISH DIRECT|PRIMARY_OUTPUT|79378|4816|10317|389682649|4816 / 389687465|10317 / 89695|
+|3|SNOWBALL DANISH LUCENE FILTER|PRIMARY_OUTPUT|78557|4961|11138|389682504|4961 / 389687465|11138 / 89695|

 </details>

@@ -195,7 +185,7 @@ This mode contains **5 result rows**, **3 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Balanced accuracy | Over-stemming (OI) | Under-stemming (UI) |
 |---:|---|---:|---:|---:|
 |1|Radixor|0.996482|0.000000%|0.703596%|
-|2|SNOWBALL DANISH DIRECT|0.938010|0.001235%|12.396694%|
+|2|SNOWBALL DANISH DIRECT|0.942383|0.001240%|11.522225%|
 |3|SNOWBALL DANISH LUCENE FILTER|0.938010|0.001235%|12.396694%|

 </div>
@@ -205,7 +195,7 @@ This mode contains **5 result rows**, **3 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | Precision | Recall | Specificity | Balanced accuracy | Pairwise accuracy | Error rate |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|1.000000|0.992964|1.000000|0.996482|0.999998|0.000002|
-|2|SNOWBALL DANISH DIRECT|PRIMARY_OUTPUT|0.942392|0.876033|0.999988|0.938010|0.999959|0.000041|
+|2|SNOWBALL DANISH DIRECT|PRIMARY_OUTPUT|0.942693|0.884778|0.999988|0.942383|0.999961|0.000039|
 |3|SNOWBALL DANISH LUCENE FILTER|PRIMARY_OUTPUT|0.942392|0.876033|0.999988|0.938010|0.999959|0.000041|

 </details>
@@ -215,7 +205,7 @@ This mode contains **5 result rows**, **3 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | F0.5 | F1 | F2 | Jaccard | Fowlkes–Mallows | MCC |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|0.998585|0.996470|0.994363|0.992964|0.996476|0.996475|
-|2|SNOWBALL DANISH DIRECT|PRIMARY_OUTPUT|0.928328|0.908002|0.888547|0.831505|0.908607|0.908587|
+|2|SNOWBALL DANISH DIRECT|PRIMARY_OUTPUT|0.930511|0.912818|0.895784|0.839618|0.913277|0.913257|
 |3|SNOWBALL DANISH LUCENE FILTER|PRIMARY_OUTPUT|0.928328|0.908002|0.888547|0.831505|0.908607|0.908587|

 </details>
@@ -225,7 +215,7 @@ This mode contains **5 result rows**, **3 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | TP | FP | FN | TN | Over error / possible | Under error / possible |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|88910|0|630|388404335|0 / 388404335|630 / 89540|
-|2|SNOWBALL DANISH DIRECT|PRIMARY_OUTPUT|78440|4795|11100|388399540|4795 / 388404335|11100 / 89540|
+|2|SNOWBALL DANISH DIRECT|PRIMARY_OUTPUT|79223|4816|10317|388399519|4816 / 388404335|10317 / 89540|
 |3|SNOWBALL DANISH LUCENE FILTER|PRIMARY_OUTPUT|78440|4795|11100|388399540|4795 / 388404335|11100 / 89540|

 </details>
@@ -316,7 +306,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `DA_DK`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/dutch.md
+++ b/docs/benchmarks/languages/dutch.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `nl-nl-default` | `1.0.0` | `NL_NL` | 4,992 | 31,466 | 9,981 | 21,485 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `nl-nl-default` | `1.0.0` | `NL_NL` | 4,992 | 31,466 | 9,981 | 21,485 | 21,485 |

 ## Radixor Patch Command Distribution

@@ -30,35 +30,25 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 99.120% | 98.711% | 100.000% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 99.120% | 98.711% | 100.000% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene HunspellStemFilter | 46.590% | 22.718% | 97.976% | Benchmark-only Dutch Hunspell dictionary compared via Lucene HunspellStemFilter. |
 | Official Snowball direct | 15.954% | 8.992% | 30.939% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
 | Lucene SnowballFilter | 12.620% | 5.441% | 28.073% | Lucene TokenFilter integration path around the Snowball algorithm. |

-
-
-
-
-
 ## Speed

 Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 independent forks, and 1 thread. Relative factor is computed against the single Radixor row on this language page. Values below 1.000 are faster than that Radixor baseline; values above 1.000 are slower.

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `radixor[DUTCH]` | 1.410 | 0.139 | 65.6 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 24.183 | 2.889 | 1125.6 | 17.156 | Benchmark-only Dutch Hunspell dictionary compared via Lucene HunspellStemFilter. |
-| Official Snowball direct | `snowballDirect[DUTCH]` | 4.560 | 0.205 | 212.2 | 3.235 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[DUTCH]` | 7.762 | 0.262 | 361.3 | 5.506 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-
-
-
-
-
+| Radixor | `radixor[DUTCH]` | 1.340 | 0.127 | 62.4 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 22.275 | 2.325 | 1036.8 | 16.621 | Benchmark-only Dutch Hunspell dictionary compared via Lucene HunspellStemFilter. |
+| Official Snowball direct | `snowballDirect[DUTCH]` | 4.298 | 0.185 | 200.0 | 3.207 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[DUTCH]` | 7.317 | 0.255 | 340.6 | 5.460 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -340,7 +330,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `NL_NL`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/english.md
+++ b/docs/benchmarks/languages/english.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `us-uk-default` | `1.0.0` | `US_UK` | 396,939 | 1,004,374 | 793,874 | 210,500 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `us-uk-default` | `1.0.0` | `US_UK` | 396,939 | 1,004,374 | 793,874 | 210,500 | 210,500 |

 ## Radixor Patch Command Distribution

@@ -30,47 +30,39 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 97.478% | 97.197% | 97.552% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 97.478% | 97.197% | 97.552% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene EnglishMinimalStemFilter | 90.981% | 65.189% | 97.820% | Minimal English plural reduction, not a full stemmer. |
 | Lucene KStemFilter | 80.076% | 76.608% | 80.996% | Krovetz-style English stemming TokenFilter; broader than minimal suffix reducers. |
 | Lucene HunspellStemFilter | 80.243% | 12.750% | 98.139% | Benchmark-only English Hunspell dictionary compared via Lucene HunspellStemFilter. |
 | Lucene EnglishPossessiveFilter | 79.032% | 0.003% | 99.987% | Possessive-ending remover only, not a full stemmer. |
-| Snowball English / Porter2 | 40.342% | 46.296% | 38.763% | Porter2 rule-based suffix stemmer, distinct from original Porter. |
+| Snowball English / Porter2 | 40.346% | 46.302% | 38.767% | Porter2 rule-based suffix stemmer, distinct from original Porter. |
 | Lucene PorterStemFilter | 39.538% | 46.201% | 37.772% | Lucene TokenFilter path for Porter suffix rules; not dictionary-root equivalent. |
 | Lucene PorterStemmer direct copy | 39.538% | 46.201% | 37.772% | Direct Porter suffix-rule implementation generated under build for benchmark-only use. |
 | OpenNLP PorterStemmer | 39.538% | 46.201% | 37.772% | Apache OpenNLP Porter suffix-rule implementation. |
 | Snowball original Porter | 39.529% | 46.179% | 37.766% | Classic Porter rule-based suffix stemmer. |
 | Paice/Husk Lancaster | 28.055% | 37.039% | 25.673% | Aggressive Paice/Husk rule stemmer that often produces shorter stems. |

-
-
-
-
 ## Speed

 Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 independent forks, and 1 thread. Relative factor is computed against the single Radixor row on this language page. Values below 1.000 are faster than that Radixor baseline; values above 1.000 are slower.

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `radixorUsUkProfiPreferredStem` | 17.489 | 1.380 | 83.1 | 1.000 | Full dictionary patch-command stemmer using compiled patch commands. |
-| Lucene EnglishPossessiveFilter | `luceneEnglishPossessiveFilter` | 17.151 | 0.215 | 81.5 | 0.981 | Possessive-ending remover only; not a full stemmer. |
-| Lucene EnglishMinimalStemFilter | `luceneEnglishMinimalStemFilter` | 18.522 | 0.152 | 88.0 | 1.059 | Narrow plural reduction filter; not a full stemmer. |
-| Lucene PorterStemmer direct copy | `lucenePorterStemmerCopied` | 17.651 | 0.129 | 83.9 | 1.009 | Benchmark-only generated copy of Lucene package-private Porter implementation. |
-| OpenNLP PorterStemmer | `opennlpPorterStemmer` | 17.681 | 0.139 | 84.0 | 1.011 | Apache OpenNLP Porter implementation. |
-| Snowball original Porter | `snowballOriginalPorter` | 33.290 | 1.916 | 158.1 | 1.904 | Classic Porter suffix-rule stemmer; historical English baseline, not a dictionary-equivalent stemmer. |
-| Lucene PorterStemFilter | `lucenePorterStemFilter` | 32.408 | 0.412 | 154.0 | 1.853 | Lucene TokenFilter integration path for Porter; includes TokenStream overhead. |
-| Lucene KStemFilter | `luceneKStemFilter` | 45.877 | 0.425 | 217.9 | 2.623 | Krovetz-style English TokenFilter; broader than minimal suffix filters. |
-| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 76.852 | 1.028 | 365.1 | 4.394 | Benchmark-only English Hunspell comparison using the benchmark Hunspell corpus. |
-| Snowball English / Porter2 | `snowballEnglishPorter2` | 46.568 | 2.414 | 221.2 | 2.663 | Porter2 suffix-rule stemmer, distinct from original Porter. |
-| Paice/Husk Lancaster | `paiceHuskLancaster` | 144.951 | 2.710 | 688.6 | 8.288 | Aggressive rule-based English stemmer. |
-
-
-
-
+| Radixor | `radixorUsUkProfiPreferredStem` | 14.397 | 0.915 | 68.4 | 1.000 | Full dictionary patch-command stemmer using compiled patch commands. |
+| Lucene EnglishPossessiveFilter | `luceneEnglishPossessiveFilter` | 15.034 | 0.322 | 71.4 | 1.044 | Possessive-ending remover only; not a full stemmer. |
+| Lucene EnglishMinimalStemFilter | `luceneEnglishMinimalStemFilter` | 16.352 | 0.244 | 77.7 | 1.136 | Narrow plural reduction filter; not a full stemmer. |
+| Lucene PorterStemmer direct copy | `lucenePorterStemmerCopied` | 16.491 | 0.149 | 78.3 | 1.145 | Benchmark-only generated copy of Lucene package-private Porter implementation. |
+| OpenNLP PorterStemmer | `opennlpPorterStemmer` | 16.481 | 0.175 | 78.3 | 1.145 | Apache OpenNLP Porter implementation. |
+| Snowball original Porter | `snowballOriginalPorter` | 30.634 | 1.620 | 145.5 | 2.128 | Classic Porter suffix-rule stemmer; historical English baseline, not a dictionary-equivalent stemmer. |
+| Lucene PorterStemFilter | `lucenePorterStemFilter` | 29.666 | 0.536 | 140.9 | 2.061 | Lucene TokenFilter integration path for Porter; includes TokenStream overhead. |
+| Lucene KStemFilter | `luceneKStemFilter` | 41.485 | 0.509 | 197.1 | 2.882 | Krovetz-style English TokenFilter; broader than minimal suffix filters. |
+| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 74.399 | 1.223 | 353.4 | 5.168 | Benchmark-only English Hunspell comparison using the benchmark Hunspell corpus. |
+| Snowball English / Porter2 | `snowballEnglishPorter2` | 43.117 | 1.983 | 204.8 | 2.995 | Porter2 suffix-rule stemmer, distinct from original Porter. |
+| Paice/Husk Lancaster | `paiceHuskLancaster` | 137.952 | 2.443 | 655.4 | 9.582 | Aggressive rule-based English stemmer. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -104,7 +96,7 @@ This mode contains **15 result rows**, **11 evaluated stemmers**, and **3 output
 |2|ENGLISH LUCENE PORTER COPIED|0.954796|0.000207%|9.040545%|
 |3|ENGLISH LUCENE PORTER FILTER|0.954796|0.000207%|9.040545%|
 |4|ENGLISH OPENNLP PORTER|0.954796|0.000207%|9.040545%|
-|5|ENGLISH SNOWBALL PORTER2|0.954708|0.000212%|9.058097%|
+|5|ENGLISH SNOWBALL PORTER2|0.954732|0.000212%|9.053310%|
 |6|ENGLISH SNOWBALL ORIGINAL PORTER|0.954659|0.000206%|9.067990%|
 |7|ENGLISH PAICE HUSK LANCASTER|0.952535|0.000960%|9.492110%|
 |8|ENGLISH LUCENE KSTEM FILTER|0.878645|0.000110%|24.270875%|
@@ -122,7 +114,7 @@ This mode contains **15 result rows**, **11 evaluated stemmers**, and **3 output
 |2|ENGLISH LUCENE PORTER COPIED|PRIMARY_OUTPUT|0.440121|0.909595|0.999998|0.954796|0.999998|0.000002|
 |3|ENGLISH LUCENE PORTER FILTER|PRIMARY_OUTPUT|0.440121|0.909595|0.999998|0.954796|0.999998|0.000002|
 |4|ENGLISH OPENNLP PORTER|PRIMARY_OUTPUT|0.440121|0.909595|0.999998|0.954796|0.999998|0.000002|
-|5|ENGLISH SNOWBALL PORTER2|PRIMARY_OUTPUT|0.434174|0.909419|0.999998|0.954708|0.999998|0.000002|
+|5|ENGLISH SNOWBALL PORTER2|PRIMARY_OUTPUT|0.434309|0.909467|0.999998|0.954732|0.999998|0.000002|
 |6|ENGLISH SNOWBALL ORIGINAL PORTER|PRIMARY_OUTPUT|0.441440|0.909320|0.999998|0.954659|0.999998|0.000002|
 |7|ENGLISH PAICE HUSK LANCASTER|PRIMARY_OUTPUT|0.144284|0.905079|0.999990|0.952535|0.999990|0.000010|
 |8|ENGLISH LUCENE KSTEM FILTER|PRIMARY_OUTPUT|0.551014|0.757291|0.999999|0.878645|0.999998|0.000002|
@@ -140,7 +132,7 @@ This mode contains **15 result rows**, **11 evaluated stemmers**, and **3 output
 |2|ENGLISH LUCENE PORTER COPIED|PRIMARY_OUTPUT|0.490783|0.593208|0.749662|0.421675|0.632717|0.632716|
 |3|ENGLISH LUCENE PORTER FILTER|PRIMARY_OUTPUT|0.490783|0.593208|0.749662|0.421675|0.632717|0.632716|
 |4|ENGLISH OPENNLP PORTER|PRIMARY_OUTPUT|0.490783|0.593208|0.749662|0.421675|0.632717|0.632716|
-|5|ENGLISH SNOWBALL PORTER2|PRIMARY_OUTPUT|0.484849|0.587747|0.746086|0.416176|0.628368|0.628367|
+|5|ENGLISH SNOWBALL PORTER2|PRIMARY_OUTPUT|0.484986|0.587880|0.746192|0.416310|0.628482|0.628481|
 |6|ENGLISH SNOWBALL ORIGINAL PORTER|PRIMARY_OUTPUT|0.492079|0.594348|0.750277|0.422827|0.633570|0.633569|
 |7|ENGLISH PAICE HUSK LANCASTER|PRIMARY_OUTPUT|0.173443|0.248891|0.440518|0.142133|0.361370|0.361368|
 |8|ENGLISH LUCENE KSTEM FILTER|PRIMARY_OUTPUT|0.582762|0.637891|0.704541|0.468312|0.645971|0.645970|
@@ -158,7 +150,7 @@ This mode contains **15 result rows**, **11 evaluated stemmers**, and **3 output
 |2|ENGLISH LUCENE PORTER COPIED|PRIMARY_OUTPUT|285026|362583|28329|175199061547|362583 / 175199424130|28329 / 313355|
 |3|ENGLISH LUCENE PORTER FILTER|PRIMARY_OUTPUT|285026|362583|28329|175199061547|362583 / 175199424130|28329 / 313355|
 |4|ENGLISH OPENNLP PORTER|PRIMARY_OUTPUT|285026|362583|28329|175199061547|362583 / 175199424130|28329 / 313355|
-|5|ENGLISH SNOWBALL PORTER2|PRIMARY_OUTPUT|284971|371381|28384|175199052749|371381 / 175199424130|28384 / 313355|
+|5|ENGLISH SNOWBALL PORTER2|PRIMARY_OUTPUT|284986|371197|28369|175199052933|371197 / 175199424130|28369 / 313355|
 |6|ENGLISH SNOWBALL ORIGINAL PORTER|PRIMARY_OUTPUT|284940|360538|28415|175199063592|360538 / 175199424130|28415 / 313355|
 |7|ENGLISH PAICE HUSK LANCASTER|PRIMARY_OUTPUT|283611|1682034|29744|175197742096|1682034 / 175199424130|29744 / 313355|
 |8|ENGLISH LUCENE KSTEM FILTER|PRIMARY_OUTPUT|237301|193361|76054|175199230769|193361 / 175199424130|76054 / 313355|
@@ -251,7 +243,7 @@ This mode contains **15 result rows**, **11 evaluated stemmers**, and **3 output
 |2|ENGLISH LUCENE PORTER COPIED|0.955064|0.000222%|8.987032%|
 |3|ENGLISH LUCENE PORTER FILTER|0.955064|0.000222%|8.987032%|
 |4|ENGLISH OPENNLP PORTER|0.955064|0.000222%|8.987032%|
-|5|ENGLISH SNOWBALL PORTER2|0.955016|0.000228%|8.996666%|
+|5|ENGLISH SNOWBALL PORTER2|0.955040|0.000228%|8.991849%|
 |6|ENGLISH SNOWBALL ORIGINAL PORTER|0.954926|0.000221%|9.014651%|
 |7|ENGLISH PAICE HUSK LANCASTER|0.952850|0.001032%|9.428933%|
 |8|ENGLISH LUCENE KSTEM FILTER|0.881028|0.000120%|23.794246%|
@@ -269,7 +261,7 @@ This mode contains **15 result rows**, **11 evaluated stemmers**, and **3 output
 |2|ENGLISH LUCENE PORTER COPIED|PRIMARY_OUTPUT|0.440920|0.910130|0.999998|0.955064|0.999998|0.000002|
 |3|ENGLISH LUCENE PORTER FILTER|PRIMARY_OUTPUT|0.440920|0.910130|0.999998|0.955064|0.999998|0.000002|
 |4|ENGLISH OPENNLP PORTER|PRIMARY_OUTPUT|0.440920|0.910130|0.999998|0.955064|0.999998|0.000002|
-|5|ENGLISH SNOWBALL PORTER2|PRIMARY_OUTPUT|0.435017|0.910033|0.999998|0.955016|0.999998|0.000002|
+|5|ENGLISH SNOWBALL PORTER2|PRIMARY_OUTPUT|0.435153|0.910082|0.999998|0.955040|0.999998|0.000002|
 |6|ENGLISH SNOWBALL ORIGINAL PORTER|PRIMARY_OUTPUT|0.442235|0.909853|0.999998|0.954926|0.999998|0.000002|
 |7|ENGLISH PAICE HUSK LANCASTER|PRIMARY_OUTPUT|0.144700|0.905711|0.999990|0.952850|0.999990|0.000010|
 |8|ENGLISH LUCENE KSTEM FILTER|PRIMARY_OUTPUT|0.551013|0.762058|0.999999|0.881028|0.999998|0.000002|
@@ -287,7 +279,7 @@ This mode contains **15 result rows**, **11 evaluated stemmers**, and **3 output
 |2|ENGLISH LUCENE PORTER COPIED|PRIMARY_OUTPUT|0.491609|0.594049|0.750417|0.422524|0.633478|0.633477|
 |3|ENGLISH LUCENE PORTER FILTER|PRIMARY_OUTPUT|0.491609|0.594049|0.750417|0.422524|0.633478|0.633477|
 |4|ENGLISH OPENNLP PORTER|PRIMARY_OUTPUT|0.491609|0.594049|0.750417|0.422524|0.633478|0.633477|
-|5|ENGLISH SNOWBALL PORTER2|PRIMARY_OUTPUT|0.485725|0.588647|0.746915|0.417080|0.629190|0.629189|
+|5|ENGLISH SNOWBALL PORTER2|PRIMARY_OUTPUT|0.485863|0.588782|0.747021|0.417215|0.629305|0.629304|
 |6|ENGLISH SNOWBALL ORIGINAL PORTER|PRIMARY_OUTPUT|0.492900|0.595181|0.751027|0.423671|0.634326|0.634325|
 |7|ENGLISH PAICE HUSK LANCASTER|PRIMARY_OUTPUT|0.173928|0.249533|0.441413|0.142553|0.362017|0.362015|
 |8|ENGLISH LUCENE KSTEM FILTER|PRIMARY_OUTPUT|0.583322|0.639575|0.707836|0.470129|0.648000|0.647999|
@@ -305,7 +297,7 @@ This mode contains **15 result rows**, **11 evaluated stemmers**, and **3 output
 |2|ENGLISH LUCENE PORTER COPIED|PRIMARY_OUTPUT|283398|359344|27984|161561630294|359344 / 161561989638|27984 / 311382|
 |3|ENGLISH LUCENE PORTER FILTER|PRIMARY_OUTPUT|283398|359344|27984|161561630294|359344 / 161561989638|27984 / 311382|
 |4|ENGLISH OPENNLP PORTER|PRIMARY_OUTPUT|283398|359344|27984|161561630294|359344 / 161561989638|27984 / 311382|
-|5|ENGLISH SNOWBALL PORTER2|PRIMARY_OUTPUT|283368|368027|28014|161561621611|368027 / 161561989638|28014 / 311382|
+|5|ENGLISH SNOWBALL PORTER2|PRIMARY_OUTPUT|283383|367843|27999|161561621795|367843 / 161561989638|27999 / 311382|
 |6|ENGLISH SNOWBALL ORIGINAL PORTER|PRIMARY_OUTPUT|283312|357325|28070|161561632313|357325 / 161561989638|28070 / 311382|
 |7|ENGLISH PAICE HUSK LANCASTER|PRIMARY_OUTPUT|282022|1666990|29360|161560322648|1666990 / 161561989638|29360 / 311382|
 |8|ENGLISH LUCENE KSTEM FILTER|PRIMARY_OUTPUT|237291|193354|74091|161561796284|193354 / 161561989638|74091 / 311382|
@@ -408,7 +400,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `US_UK`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/finnish.md
+++ b/docs/benchmarks/languages/finnish.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `fi-fi-default` | `1.0.0` | `FI_FI` | 57,027 | 1,865,215 | 110,525 | 1,754,690 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `fi-fi-default` | `1.0.0` | `FI_FI` | 57,027 | 1,865,215 | 110,525 | 1,754,690 | 1,754,690 |

 ## Radixor Patch Command Distribution

@@ -30,14 +30,10 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 98.661% | 98.803% | 96.408% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 98.661% | 98.803% | 96.408% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene SnowballFilter | 10.991% | 10.268% | 22.471% | Lucene TokenFilter integration path around the Snowball algorithm. |
-| Official Snowball direct | 10.991% | 10.268% | 22.471% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
-| Lucene FinnishLightStemFilter | 4.351% | 4.294% | 5.264% | Light suffix stemmer; intentionally narrower than a dictionary-derived stemmer. |
-
-
-
-
+| Official Snowball direct | 10.995% | 10.272% | 22.462% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
+| Lucene FinnishLightStemFilter | 4.351% | 4.294% | 5.264% | Light suffix stemmer; intentionally narrower than Radixor's dictionary-trained transformation model. |

 ## Speed

@@ -45,18 +41,14 @@ Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 i

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `finnishRadixor` | 289.539 | 4.136 | 165.0 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene FinnishLightStemFilter | `finnishLuceneFinnishLightStemFilter` | 175.789 | 4.827 | 100.2 | 0.607 | Light Finnish suffix stemmer. |
-| Official Snowball direct | `snowballDirect[FINNISH]` | 259.889 | 8.924 | 148.1 | 0.898 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[FINNISH]` | 332.524 | 9.490 | 189.5 | 1.148 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-
-
-
-
+| Radixor | `finnishRadixor` | 225.954 | 2.940 | 128.8 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene FinnishLightStemFilter | `finnishLuceneFinnishLightStemFilter` | 168.756 | 6.027 | 96.2 | 0.747 | Light Finnish suffix stemmer. |
+| Official Snowball direct | `snowballDirect[FINNISH]` | 247.984 | 16.083 | 141.3 | 1.097 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[FINNISH]` | 321.331 | 9.790 | 183.1 | 1.422 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -75,7 +67,7 @@ Runtime performance and linguistic grouping quality are independent dimensions.
 The default model is `fi-fi-default`, loaded from classpath resource `org/egothor/stemmer/models/fi-fi-default/stemmer.gz`. The following findings compare only deterministic `PRIMARY_OUTPUT` rows over identical included groups; candidate policies are reported separately as capability analyses.

 - **ALL_WORDS:** `Radixor` ranks first by balanced accuracy at **0.984838** among 4 deterministic stemmers. The runner-up is `SNOWBALL FINNISH LUCENE FILTER` at 0.740279, a difference of 0.244559. This rank does not imply leadership in throughput or every secondary metric.
- **LOWERCASE_GROUPS_ONLY:** `Radixor` ranks first by balanced accuracy at **0.988242** among 4 deterministic stemmers. The runner-up is `SNOWBALL FINNISH DIRECT` at 0.738344, a difference of 0.249898. This rank does not imply leadership in throughput or every secondary metric.
+- **LOWERCASE_GROUPS_ONLY:** `Radixor` ranks first by balanced accuracy at **0.988242** among 4 deterministic stemmers. The runner-up is `SNOWBALL FINNISH DIRECT` at 0.738543, a difference of 0.249699. This rank does not imply leadership in throughput or every secondary metric.
 ### `ALL_WORDS`

 This mode contains **6 result rows**, **4 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.
@@ -88,7 +80,7 @@ This mode contains **6 result rows**, **4 evaluated stemmers**, and **3 output p
 |---:|---|---:|---:|---:|
 |1|Radixor|0.984838|&lt;0.000001%|3.032474%|
 |2|SNOWBALL FINNISH LUCENE FILTER|0.740279|0.000081%|51.944179%|
-|3|SNOWBALL FINNISH DIRECT|0.739671|0.000060%|52.065724%|
+|3|SNOWBALL FINNISH DIRECT|0.739870|0.000060%|52.025976%|
 |4|FINNISH LUCENE FINNISH LIGHT STEM FILTER|0.695725|0.000094%|60.854936%|

 </div>
@@ -99,7 +91,7 @@ This mode contains **6 result rows**, **4 evaluated stemmers**, and **3 output p
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|0.999974|0.969675|1.000000|0.984838|0.999999|0.000001|
 |2|SNOWBALL FINNISH LUCENE FILTER|PRIMARY_OUTPUT|0.921471|0.480558|0.999999|0.740279|0.999989|0.000011|
-|3|SNOWBALL FINNISH DIRECT|PRIMARY_OUTPUT|0.940611|0.479343|0.999999|0.739671|0.999989|0.000011|
+|3|SNOWBALL FINNISH DIRECT|PRIMARY_OUTPUT|0.940647|0.479740|0.999999|0.739870|0.999989|0.000011|
 |4|FINNISH LUCENE FINNISH LIGHT STEM FILTER|PRIMARY_OUTPUT|0.890914|0.391451|0.999999|0.695725|0.999987|0.000013|

 </details>
@@ -110,7 +102,7 @@ This mode contains **6 result rows**, **4 evaluated stemmers**, and **3 output p
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|0.993763|0.984591|0.975587|0.969650|0.984708|0.984708|
 |2|SNOWBALL FINNISH LUCENE FILTER|PRIMARY_OUTPUT|0.778598|0.631685|0.531413|0.461652|0.665448|0.665443|
-|3|SNOWBALL FINNISH DIRECT|PRIMARY_OUTPUT|0.788800|0.635056|0.531468|0.465262|0.671472|0.671468|
+|3|SNOWBALL FINNISH DIRECT|PRIMARY_OUTPUT|0.789035|0.635413|0.531862|0.465645|0.671764|0.671760|
 |4|FINNISH LUCENE FINNISH LIGHT STEM FILTER|PRIMARY_OUTPUT|0.709787|0.543915|0.440884|0.373546|0.590550|0.590545|

 </details>
@@ -121,7 +113,7 @@ This mode contains **6 result rows**, **4 evaluated stemmers**, and **3 output p
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|30511413|804|954186|1599841738533|804 / 1599841739337|954186 / 31465599|
 |2|SNOWBALL FINNISH LUCENE FILTER|PRIMARY_OUTPUT|15121052|1288634|16344547|1599840450703|1288634 / 1599841739337|16344547 / 31465599|
-|3|SNOWBALL FINNISH DIRECT|PRIMARY_OUTPUT|15082807|952306|16382792|1599840787031|952306 / 1599841739337|16382792 / 31465599|
+|3|SNOWBALL FINNISH DIRECT|PRIMARY_OUTPUT|15095314|952479|16370285|1599840786858|952479 / 1599841739337|16370285 / 31465599|
 |4|FINNISH LUCENE FINNISH LIGHT STEM FILTER|PRIMARY_OUTPUT|12317229|1508153|19148370|1599840231184|1508153 / 1599841739337|19148370 / 31465599|

 </details>
@@ -199,7 +191,7 @@ This mode contains **6 result rows**, **4 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Balanced accuracy | Over-stemming (OI) | Under-stemming (UI) |
 |---:|---|---:|---:|---:|
 |1|Radixor|0.988242|&lt;0.000001%|2.351587%|
-|2|SNOWBALL FINNISH DIRECT|0.738344|0.000062%|52.331112%|
+|2|SNOWBALL FINNISH DIRECT|0.738543|0.000062%|52.291340%|
 |3|SNOWBALL FINNISH LUCENE FILTER|0.738344|0.000062%|52.331112%|
 |4|FINNISH LUCENE FINNISH LIGHT STEM FILTER|0.694308|0.000077%|61.138333%|

@@ -210,7 +202,7 @@ This mode contains **6 result rows**, **4 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | Precision | Recall | Specificity | Balanced accuracy | Pairwise accuracy | Error rate |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|0.999973|0.976484|1.000000|0.988242|1.000000|0.000000|
-|2|SNOWBALL FINNISH DIRECT|PRIMARY_OUTPUT|0.939951|0.476689|0.999999|0.738344|0.999989|0.000011|
+|2|SNOWBALL FINNISH DIRECT|PRIMARY_OUTPUT|0.939988|0.477087|0.999999|0.738543|0.999989|0.000011|
 |3|SNOWBALL FINNISH LUCENE FILTER|PRIMARY_OUTPUT|0.939951|0.476689|0.999999|0.738344|0.999989|0.000011|
 |4|FINNISH LUCENE FINNISH LIGHT STEM FILTER|PRIMARY_OUTPUT|0.911893|0.388617|0.999999|0.694308|0.999987|0.000013|

@@ -221,7 +213,7 @@ This mode contains **6 result rows**, **4 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | F0.5 | F1 | F2 | Jaccard | Fowlkes–Mallows | MCC |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|0.995185|0.988089|0.981093|0.976459|0.988159|0.988159|
-|2|SNOWBALL FINNISH DIRECT|PRIMARY_OUTPUT|0.786987|0.632573|0.528815|0.462601|0.669376|0.669372|
+|2|SNOWBALL FINNISH DIRECT|PRIMARY_OUTPUT|0.787224|0.632932|0.529209|0.462985|0.669668|0.669664|
 |3|SNOWBALL FINNISH LUCENE FILTER|PRIMARY_OUTPUT|0.786987|0.632573|0.528815|0.462601|0.669376|0.669372|
 |4|FINNISH LUCENE FINNISH LIGHT STEM FILTER|PRIMARY_OUTPUT|0.718421|0.544981|0.438999|0.374553|0.595296|0.595291|

@@ -232,7 +224,7 @@ This mode contains **6 result rows**, **4 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | TP | FP | FN | TN | Over error / possible | Under error / possible |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|30037514|804|723369|1504706134249|804 / 1504706135053|723369 / 30760883|
-|2|SNOWBALL FINNISH DIRECT|PRIMARY_OUTPUT|14663371|936765|16097512|1504705198288|936765 / 1504706135053|16097512 / 30760883|
+|2|SNOWBALL FINNISH DIRECT|PRIMARY_OUTPUT|14675605|936938|16085278|1504705198115|936938 / 1504706135053|16085278 / 30760883|
 |3|SNOWBALL FINNISH LUCENE FILTER|PRIMARY_OUTPUT|14663371|936765|16097512|1504705198288|936765 / 1504706135053|16097512 / 30760883|
 |4|FINNISH LUCENE FINNISH LIGHT STEM FILTER|PRIMARY_OUTPUT|11954192|1155011|18806691|1504704980042|1155011 / 1504706135053|18806691 / 30760883|

@@ -324,7 +316,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `FI_FI`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/french.md
+++ b/docs/benchmarks/languages/french.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `fr-fr-default` | `1.0.0` | `FR_FR` | 59,240 | 474,110 | 108,141 | 365,969 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `fr-fr-default` | `1.0.0` | `FR_FR` | 59,240 | 474,110 | 108,141 | 365,969 | 365,969 |

 ## Radixor Patch Command Distribution

@@ -30,16 +30,12 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 94.831% | 94.859% | 94.734% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 94.831% | 94.859% | 94.734% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene HunspellStemFilter | 68.923% | 63.617% | 86.876% | Benchmark-only French Hunspell dictionary compared via Lucene HunspellStemFilter. |
 | Lucene FrenchMinimalStemFilter | 11.472% | 6.236% | 29.192% | Minimal suffix reducer; narrow baseline, not a full stemmer. |
 | Lucene SnowballFilter | 8.551% | 5.183% | 19.952% | Lucene TokenFilter integration path around the Snowball algorithm. |
 | Official Snowball direct | 8.462% | 5.067% | 19.952% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
-| Lucene FrenchLightStemFilter | 6.377% | 3.965% | 14.540% | Light suffix stemmer; intentionally narrower than a dictionary-derived stemmer. |
-
-
-
-
+| Lucene FrenchLightStemFilter | 6.377% | 3.965% | 14.540% | Light suffix stemmer; intentionally narrower than Radixor's dictionary-trained transformation model. |

 ## Speed

@@ -47,20 +43,16 @@ Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 i

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `frenchRadixor` | 49.340 | 0.986 | 134.8 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 1781.070 | 43.544 | 4866.7 | 36.098 | Benchmark-only French Hunspell dictionary compared via Lucene HunspellStemFilter. |
-| Lucene FrenchMinimalStemFilter | `frenchLuceneFrenchMinimalStemFilter` | 19.093 | 0.681 | 52.2 | 0.387 | Minimal French suffix reducer; narrow baseline. |
-| Lucene FrenchLightStemFilter | `frenchLuceneFrenchLightStemFilter` | 29.553 | 0.465 | 80.8 | 0.599 | Light French suffix stemmer. |
-| Official Snowball direct | `snowballDirect[FRENCH]` | 121.376 | 0.865 | 331.7 | 2.460 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[FRENCH]` | 126.574 | 4.671 | 345.9 | 2.565 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-
-
-
-
+| Radixor | `frenchRadixor` | 37.443 | 0.520 | 102.3 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 1673.192 | 57.385 | 4572.0 | 44.686 | Benchmark-only French Hunspell dictionary compared via Lucene HunspellStemFilter. |
+| Lucene FrenchMinimalStemFilter | `frenchLuceneFrenchMinimalStemFilter` | 18.034 | 0.181 | 49.3 | 0.482 | Minimal French suffix reducer; narrow baseline. |
+| Lucene FrenchLightStemFilter | `frenchLuceneFrenchLightStemFilter` | 27.961 | 0.493 | 76.4 | 0.747 | Light French suffix stemmer. |
+| Official Snowball direct | `snowballDirect[FRENCH]` | 112.255 | 4.045 | 306.7 | 2.998 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[FRENCH]` | 119.555 | 4.560 | 326.7 | 3.193 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -358,7 +350,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `FR_FR`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/german.md
+++ b/docs/benchmarks/languages/german.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `de-de-default` | `1.0.0` | `DE_DE` | 54,092 | 333,036 | 90,535 | 242,501 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `de-de-default` | `1.0.0` | `DE_DE` | 54,092 | 333,036 | 90,535 | 242,501 | 242,501 |

 ## Radixor Patch Command Distribution

@@ -30,41 +30,33 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 92.725% | 92.847% | 92.396% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 92.725% | 92.847% | 92.396% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene HunspellStemFilter | 47.064% | 29.661% | 93.678% | Benchmark-only German Hunspell dictionary compared via Lucene HunspellStemFilter. |
 | CISTEM (German) | 24.675% | 23.724% | 27.222% | Benchmark-only CISTEM implementation. |
-| Lucene GermanLightStemFilter | 37.434% | 35.465% | 42.707% | Light suffix stemmer; intentionally narrower than a dictionary-derived stemmer. |
+| Lucene GermanLightStemFilter | 37.434% | 35.465% | 42.707% | Light suffix stemmer; intentionally narrower than Radixor's lexicon-trained transformation model. |
 | Lucene GermanMinimalStemFilter | 27.640% | 24.951% | 34.844% | Minimal suffix reducer; narrow baseline, not a full stemmer. |
 | Lucene SnowballFilter | 30.956% | 28.853% | 36.589% | Lucene TokenFilter integration path around the Snowball algorithm. |
-| Official Snowball direct | 30.481% | 29.027% | 34.376% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
+| Official Snowball direct | 30.483% | 29.030% | 34.376% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
 | Lucene GermanStemFilter | 21.559% | 19.312% | 27.576% | German Lucene stemming TokenFilter; broader than minimal/light variants. |

-
-
-
-
 ## Speed

 Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 independent forks, and 1 thread. Relative factor is computed against the single Radixor row on this language page. Values below 1.000 are faster than that Radixor baseline; values above 1.000 are slower.

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `germanRadixor` | 40.571 | 1.647 | 167.3 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| CISTEM | `germanCistem` | 305.166 | 4.590 | 1258.4 | 7.522 | Benchmark-only CISTEM implementation. |
-| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 291.791 | 21.769 | 1203.3 | 7.192 | Benchmark-only German Hunspell dictionary compared via Lucene HunspellStemFilter. |
-| Lucene GermanMinimalStemFilter | `germanLuceneGermanMinimalStemFilter` | 23.903 | 0.208 | 98.6 | 0.589 | Minimal German suffix reduction; narrow baseline. |
-| Lucene GermanLightStemFilter | `germanLuceneGermanLightStemFilter` | 24.695 | 0.322 | 101.8 | 0.609 | Light German suffix stemmer; narrower than a dictionary stemmer. |
-| Lucene GermanStemFilter | `germanLuceneGermanStemFilter` | 72.140 | 1.544 | 297.5 | 1.778 | Older German stemming TokenFilter with normalization requirements. |
-| Lucene SnowballFilter | `luceneSnowballFilter[GERMAN]` | 110.086 | 2.315 | 454.0 | 2.713 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-| Official Snowball direct | `snowballDirect[GERMAN]` | 100.122 | 2.623 | 412.9 | 2.468 | Official Snowball generated Java stemmer; direct API. |
-
-
-
-
+| Radixor | `germanRadixor` | 27.697 | 0.583 | 114.2 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| CISTEM | `germanCistem` | 289.568 | 8.761 | 1194.1 | 10.455 | Benchmark-only CISTEM implementation. |
+| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 265.653 | 10.779 | 1095.5 | 9.591 | Benchmark-only German Hunspell dictionary compared via Lucene HunspellStemFilter. |
+| Lucene GermanMinimalStemFilter | `germanLuceneGermanMinimalStemFilter` | 22.385 | 0.217 | 92.3 | 0.808 | Minimal German suffix reduction; narrow baseline. |
+| Lucene GermanLightStemFilter | `germanLuceneGermanLightStemFilter` | 23.170 | 0.383 | 95.5 | 0.837 | Light German suffix stemmer; narrower than Radixor's lexicon-trained transformation model. |
+| Lucene GermanStemFilter | `germanLuceneGermanStemFilter` | 67.453 | 0.967 | 278.2 | 2.435 | Older German stemming TokenFilter with normalization requirements. |
+| Lucene SnowballFilter | `luceneSnowballFilter[GERMAN]` | 105.203 | 2.035 | 433.8 | 3.798 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
+| Official Snowball direct | `snowballDirect[GERMAN]` | 91.847 | 2.301 | 378.7 | 3.316 | Official Snowball generated Java stemmer; direct API. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -96,7 +88,7 @@ This mode contains **12 result rows**, **8 evaluated stemmers**, and **3 output
 |---:|---|---:|---:|---:|
 |1|Radixor|0.910445|0.000002%|17.910967%|
 |2|GERMAN CISTEM|0.878527|0.000674%|24.293900%|
-|3|SNOWBALL GERMAN DIRECT|0.776006|0.000171%|44.798684%|
+|3|SNOWBALL GERMAN DIRECT|0.776012|0.000171%|44.797420%|
 |4|SNOWBALL GERMAN LUCENE FILTER|0.769071|0.000371%|46.185528%|
 |5|GERMAN LUCENE GERMAN LIGHT STEM FILTER|0.753833|0.000191%|49.233299%|
 |6|GERMAN LUCENE GERMAN STEM FILTER|0.720992|0.000443%|55.801084%|
@@ -111,7 +103,7 @@ This mode contains **12 result rows**, **8 evaluated stemmers**, and **3 output
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|0.999400|0.820890|1.000000|0.910445|0.999994|0.000006|
 |2|GERMAN CISTEM|PRIMARY_OUTPUT|0.797231|0.757061|0.999993|0.878527|0.999985|0.000015|
-|3|SNOWBALL GERMAN DIRECT|PRIMARY_OUTPUT|0.918570|0.552013|0.999998|0.776006|0.999983|0.000017|
+|3|SNOWBALL GERMAN DIRECT|PRIMARY_OUTPUT|0.918571|0.552026|0.999998|0.776012|0.999983|0.000017|
 |4|SNOWBALL GERMAN LUCENE FILTER|PRIMARY_OUTPUT|0.835220|0.538145|0.999996|0.769071|0.999980|0.000020|
 |5|GERMAN LUCENE GERMAN LIGHT STEM FILTER|PRIMARY_OUTPUT|0.902792|0.507667|0.999998|0.753833|0.999981|0.000019|
 |6|GERMAN LUCENE GERMAN STEM FILTER|PRIMARY_OUTPUT|0.777304|0.441989|0.999996|0.720992|0.999976|0.000024|
@@ -126,7 +118,7 @@ This mode contains **12 result rows**, **8 evaluated stemmers**, and **3 output
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|0.957746|0.901392|0.851302|0.820486|0.905758|0.905755|
 |2|GERMAN CISTEM|PRIMARY_OUTPUT|0.788860|0.776627|0.764768|0.634824|0.776886|0.776879|
-|3|SNOWBALL GERMAN DIRECT|PRIMARY_OUTPUT|0.810879|0.689608|0.599891|0.526260|0.712083|0.712076|
+|3|SNOWBALL GERMAN DIRECT|PRIMARY_OUTPUT|0.810886|0.689618|0.599903|0.526272|0.712092|0.712085|
 |4|SNOWBALL GERMAN LUCENE FILTER|PRIMARY_OUTPUT|0.752175|0.654552|0.579359|0.486494|0.670425|0.670416|
 |5|GERMAN LUCENE GERMAN LIGHT STEM FILTER|PRIMARY_OUTPUT|0.781189|0.649884|0.556368|0.481355|0.676991|0.676984|
 |6|GERMAN LUCENE GERMAN STEM FILTER|PRIMARY_OUTPUT|0.674901|0.563540|0.483723|0.392311|0.586140|0.586130|
@@ -141,7 +133,7 @@ This mode contains **12 result rows**, **8 evaluated stemmers**, and **3 output
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|1103976|663|240876|38436733230|663 / 38436733893|240876 / 1344852|
 |2|GERMAN CISTEM|PRIMARY_OUTPUT|1018135|258954|326717|38436474939|258954 / 38436733893|326717 / 1344852|
-|3|SNOWBALL GERMAN DIRECT|PRIMARY_OUTPUT|742376|65811|602476|38436668082|65811 / 38436733893|602476 / 1344852|
+|3|SNOWBALL GERMAN DIRECT|PRIMARY_OUTPUT|742393|65811|602459|38436668082|65811 / 38436733893|602459 / 1344852|
 |4|SNOWBALL GERMAN LUCENE FILTER|PRIMARY_OUTPUT|723725|142783|621127|38436591110|142783 / 38436733893|621127 / 1344852|
 |5|GERMAN LUCENE GERMAN LIGHT STEM FILTER|PRIMARY_OUTPUT|682737|73514|662115|38436660379|73514 / 38436733893|662115 / 1344852|
 |6|GERMAN LUCENE GERMAN STEM FILTER|PRIMARY_OUTPUT|594410|170297|750442|38436563596|170297 / 38436733893|750442 / 1344852|
@@ -231,7 +223,7 @@ This mode contains **12 result rows**, **8 evaluated stemmers**, and **3 output
 |---:|---|---:|---:|---:|
 |1|Radixor|0.966959|0.000001%|6.608210%|
 |2|GERMAN CISTEM|0.914727|0.000812%|17.053716%|
-|3|SNOWBALL GERMAN DIRECT|0.794994|0.000391%|41.000819%|
+|3|SNOWBALL GERMAN DIRECT|0.794997|0.000391%|41.000236%|
 |4|SNOWBALL GERMAN LUCENE FILTER|0.774716|0.000325%|45.056540%|
 |5|GERMAN LUCENE GERMAN LIGHT STEM FILTER|0.768968|0.000130%|46.206331%|
 |6|GERMAN LUCENE GERMAN STEM FILTER|0.716147|0.000358%|56.770194%|
@@ -246,7 +238,7 @@ This mode contains **12 result rows**, **8 evaluated stemmers**, and **3 output
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|0.999900|0.933918|1.000000|0.966959|0.999995|0.000005|
 |2|GERMAN CISTEM|PRIMARY_OUTPUT|0.892172|0.829463|0.999992|0.914727|0.999978|0.000022|
-|3|SNOWBALL GERMAN DIRECT|PRIMARY_OUTPUT|0.924303|0.589992|0.999996|0.794994|0.999963|0.000037|
+|3|SNOWBALL GERMAN DIRECT|PRIMARY_OUTPUT|0.924304|0.589998|0.999996|0.794997|0.999963|0.000037|
 |4|SNOWBALL GERMAN LUCENE FILTER|PRIMARY_OUTPUT|0.931871|0.549435|0.999997|0.774716|0.999960|0.000040|
 |5|GERMAN LUCENE GERMAN LIGHT STEM FILTER|PRIMARY_OUTPUT|0.971001|0.537937|0.999999|0.768968|0.999961|0.000039|
 |6|GERMAN LUCENE GERMAN STEM FILTER|PRIMARY_OUTPUT|0.907196|0.432298|0.999996|0.716147|0.999950|0.000050|
@@ -261,7 +253,7 @@ This mode contains **12 result rows**, **8 evaluated stemmers**, and **3 output
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|0.985968|0.965783|0.946408|0.933831|0.966346|0.966343|
 |2|GERMAN CISTEM|PRIMARY_OUTPUT|0.878883|0.859676|0.841289|0.753887|0.860246|0.860236|
-|3|SNOWBALL GERMAN DIRECT|PRIMARY_OUTPUT|0.830217|0.720244|0.635999|0.562799|0.738466|0.738450|
+|3|SNOWBALL GERMAN DIRECT|PRIMARY_OUTPUT|0.830220|0.720249|0.636004|0.562804|0.738469|0.738454|
 |4|SNOWBALL GERMAN LUCENE FILTER|PRIMARY_OUTPUT|0.817997|0.691285|0.598564|0.528217|0.715543|0.715527|
 |5|GERMAN LUCENE GERMAN LIGHT STEM FILTER|PRIMARY_OUTPUT|0.836342|0.692324|0.590620|0.529431|0.722729|0.722714|
 |6|GERMAN LUCENE GERMAN STEM FILTER|PRIMARY_OUTPUT|0.743781|0.585563|0.482850|0.413990|0.626242|0.626223|
@@ -276,7 +268,7 @@ This mode contains **12 result rows**, **8 evaluated stemmers**, and **3 output
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|801691|80|56726|10594963454|80 / 10594963534|56726 / 858417|
 |2|GERMAN CISTEM|PRIMARY_OUTPUT|712025|86055|146392|10594877479|86055 / 10594963534|146392 / 858417|
-|3|SNOWBALL GERMAN DIRECT|PRIMARY_OUTPUT|506459|41477|351958|10594922057|41477 / 10594963534|351958 / 858417|
+|3|SNOWBALL GERMAN DIRECT|PRIMARY_OUTPUT|506464|41477|351953|10594922057|41477 / 10594963534|351953 / 858417|
 |4|SNOWBALL GERMAN LUCENE FILTER|PRIMARY_OUTPUT|471644|34482|386773|10594929052|34482 / 10594963534|386773 / 858417|
 |5|GERMAN LUCENE GERMAN LIGHT STEM FILTER|PRIMARY_OUTPUT|461774|13791|396643|10594949743|13791 / 10594963534|396643 / 858417|
 |6|GERMAN LUCENE GERMAN STEM FILTER|PRIMARY_OUTPUT|371092|37962|487325|10594925572|37962 / 10594963534|487325 / 858417|
@@ -378,7 +370,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `DE_DE`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/hebrew.md
+++ b/docs/benchmarks/languages/hebrew.md
@@ -8,9 +8,9 @@ The default Hebrew model currently has no same-language third-party adapter in t

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `he-il-default` | `1.0.0` | `HE_IL` | 2,358 | 61,071 | 4,715 | 56,356 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `he-il-default` | `1.0.0` | `HE_IL` | 2,358 | 61,071 | 4,715 | 56,356 | 56,356 |

 ## Radixor Patch Command Distribution

@@ -32,23 +32,17 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun
 | --- | ---: | ---: | ---: | --- |
 | Radixor | 98.228% | 98.172% | 98.897% | Full default-model Radixor dictionary patch-command stemmer. |

-
-
-
 ## Speed

 Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 independent forks, and 1 thread.

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `hebrewRadixor` | 3.921 | 0.140 | 69.6 | 1.000 | Full default-model Radixor dictionary patch-command stemmer. |
-
-
-
+| Radixor | `hebrewRadixor` | 3.570 | 0.074 | 63.3 | 1.000 | Full default-model Radixor dictionary patch-command stemmer. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the default language model used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Hebrew patch commands use forward traversal as declared by the model metadata.
 - Results are environment-specific and should be compared only with rows from the same benchmark run.

@@ -290,7 +284,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `HE_IL`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/hungarian.md
+++ b/docs/benchmarks/languages/hungarian.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `hu-hu-default` | `1.0.0` | `HU_HU` | 19,406 | 935,713 | 38,775 | 896,938 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `hu-hu-default` | `1.0.0` | `HU_HU` | 19,406 | 935,713 | 38,775 | 896,938 | 896,938 |

 ## Radixor Patch Command Distribution

@@ -30,13 +30,10 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 99.222% | 99.537% | 91.948% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 99.222% | 99.537% | 91.948% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene SnowballFilter | 66.445% | 66.938% | 55.043% | Lucene TokenFilter integration path around the Snowball algorithm. |
 | Official Snowball direct | 66.445% | 66.938% | 55.043% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
-| Lucene HungarianLightStemFilter | 14.748% | 14.777% | 14.086% | Light suffix stemmer; intentionally narrower than a dictionary-derived stemmer. |
-
-
-
+| Lucene HungarianLightStemFilter | 14.748% | 14.777% | 14.086% | Light suffix stemmer; intentionally narrower than Radixor's dictionary-trained transformation model. |

 ## Speed

@@ -44,17 +41,14 @@ Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 i

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `hungarianRadixor` | 61.205 | 0.944 | 68.2 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene HungarianLightStemFilter | `hungarianLuceneHungarianLightStemFilter` | 92.090 | 3.410 | 102.7 | 1.505 | Light Hungarian suffix stemmer. |
-| Official Snowball direct | `snowballDirect[HUNGARIAN]` | 152.969 | 4.468 | 170.5 | 2.499 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[HUNGARIAN]` | 188.807 | 5.290 | 210.5 | 3.085 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-
-
-
+| Radixor | `hungarianRadixor` | 52.020 | 1.337 | 58.0 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene HungarianLightStemFilter | `hungarianLuceneHungarianLightStemFilter` | 87.362 | 3.444 | 97.4 | 1.679 | Light Hungarian suffix stemmer. |
+| Official Snowball direct | `snowballDirect[HUNGARIAN]` | 158.081 | 9.757 | 176.2 | 3.039 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[HUNGARIAN]` | 179.398 | 8.041 | 200.0 | 3.449 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -322,7 +316,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `HU_HU`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/italian.md
+++ b/docs/benchmarks/languages/italian.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `it-it-default` | `1.0.0` | `IT_IT` | 10,009 | 337,546 | 20,004 | 317,542 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `it-it-default` | `1.0.0` | `IT_IT` | 10,009 | 337,546 | 20,004 | 317,542 | 317,542 |

 ## Radixor Patch Command Distribution

@@ -29,31 +29,25 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 99.056% | 98.997% | 100.000% | Full Radixor dictionary patch-command stemmer. |
-| Lucene ItalianLightStemFilter | 0.466% | 0.479% | 0.270% | Light suffix stemmer; intentionally narrower than a dictionary-derived stemmer. |
+| Radixor | 99.056% | 98.997% | 100.000% | Radixor dictionary-trained patch-command stemmer. |
+| Lucene ItalianLightStemFilter | 0.466% | 0.479% | 0.270% | Light suffix stemmer; intentionally narrower than Radixor's dictionary-trained transformation model. |
 | Lucene SnowballFilter | 0.041% | 0.043% | 0.010% | Lucene TokenFilter integration path around the Snowball algorithm. |
 | Official Snowball direct | 0.041% | 0.043% | 0.010% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |

-
-
-
 ## Speed

 Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 independent forks, and 1 thread. Relative factor is computed against the single Radixor row on this language page. Values below 1.000 are faster than that Radixor baseline; values above 1.000 are slower.

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `italianRadixor` | 25.073 | 0.534 | 79.0 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene ItalianLightStemFilter | `italianLuceneItalianLightStemFilter` | 15.956 | 0.184 | 50.2 | 0.636 | Light Italian suffix stemmer. |
-| Official Snowball direct | `snowballDirect[ITALIAN]` | 115.818 | 3.174 | 364.7 | 4.619 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[ITALIAN]` | 123.974 | 4.405 | 390.4 | 4.944 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-
-
-
+| Radixor | `italianRadixor` | 22.503 | 0.434 | 70.9 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene ItalianLightStemFilter | `italianLuceneItalianLightStemFilter` | 15.008 | 0.278 | 47.3 | 0.667 | Light Italian suffix stemmer. |
+| Official Snowball direct | `snowballDirect[ITALIAN]` | 109.401 | 2.983 | 344.5 | 4.862 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[ITALIAN]` | 116.392 | 3.271 | 366.5 | 5.172 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -321,7 +315,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `IT_IT`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/norwegian-bokmal.md
+++ b/docs/benchmarks/languages/norwegian-bokmal.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `nb-no-default` | `1.0.0` | `NB_NO` | 17,929 | 90,757 | 33,376 | 57,381 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `nb-no-default` | `1.0.0` | `NB_NO` | 17,929 | 90,757 | 33,376 | 57,381 | 57,381 |

 ## Radixor Patch Command Distribution

@@ -30,14 +30,11 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 96.852% | 97.637% | 95.503% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 96.852% | 97.637% | 95.503% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene NorwegianMinimalStemFilter | 57.107% | 53.913% | 62.599% | Minimal suffix reducer; narrow baseline, not a full stemmer. |
 | Official Snowball direct | 54.824% | 51.791% | 60.040% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
 | Lucene SnowballFilter | 54.803% | 51.780% | 60.001% | Lucene TokenFilter integration path around the Snowball algorithm. |
-| Lucene NorwegianLightStemFilter | 52.136% | 50.616% | 54.749% | Light suffix stemmer; intentionally narrower than a dictionary-derived stemmer. |
-
-
-
+| Lucene NorwegianLightStemFilter | 52.136% | 50.616% | 54.749% | Light suffix stemmer; intentionally narrower than Radixor's dictionary-trained transformation model. |

 ## Speed

@@ -45,18 +42,15 @@ Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 i

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `norwegianBokmalRadixor` | 3.401 | 0.055 | 59.3 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene NorwegianMinimalStemFilter | `norwegianBokmalLuceneNorwegianMinimalStemFilter` | 2.943 | 0.023 | 51.3 | 0.865 | Minimal Norwegian suffix reducer. |
-| Lucene NorwegianLightStemFilter | `norwegianBokmalLuceneNorwegianLightStemFilter` | 3.358 | 0.036 | 58.5 | 0.987 | Light Norwegian suffix stemmer. |
-| Official Snowball direct | `snowballDirect[NORWEGIAN_BOKMAL]` | 4.378 | 0.295 | 76.3 | 1.287 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[NORWEGIAN_BOKMAL]` | 6.114 | 0.436 | 106.5 | 1.797 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-
-
-
+| Radixor | `norwegianBokmalRadixor` | 3.240 | 0.087 | 56.5 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene NorwegianMinimalStemFilter | `norwegianBokmalLuceneNorwegianMinimalStemFilter` | 2.726 | 0.022 | 47.5 | 0.841 | Minimal Norwegian suffix reducer. |
+| Lucene NorwegianLightStemFilter | `norwegianBokmalLuceneNorwegianLightStemFilter` | 3.136 | 0.028 | 54.6 | 0.968 | Light Norwegian suffix stemmer. |
+| Official Snowball direct | `snowballDirect[NORWEGIAN_BOKMAL]` | 4.711 | 0.410 | 82.1 | 1.454 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[NORWEGIAN_BOKMAL]` | 5.681 | 0.206 | 99.0 | 1.753 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -332,7 +326,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `NB_NO`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/norwegian-nynorsk.md
+++ b/docs/benchmarks/languages/norwegian-nynorsk.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `nn-no-default` | `1.0.0` | `NN_NO` | 4,688 | 19,651 | 6,089 | 13,562 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `nn-no-default` | `1.0.0` | `NN_NO` | 4,688 | 19,651 | 6,089 | 13,562 | 13,562 |

 ## Radixor Patch Command Distribution

@@ -30,29 +30,23 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 93.089% | 91.395% | 96.863% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 93.089% | 91.395% | 96.863% | Radixor dictionary-trained patch-command stemmer. |
 | Official Snowball direct | 60.974% | 60.212% | 62.670% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
 | Lucene SnowballFilter | 60.918% | 60.146% | 62.638% | Lucene TokenFilter integration path around the Snowball algorithm. |

-
-
-
 ## Speed

 Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 independent forks, and 1 thread. Relative factor is computed against the single Radixor row on this language page. Values below 1.000 are faster than that Radixor baseline; values above 1.000 are slower.

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `radixor[NORWEGIAN_NYNORSK]` | 0.617 | 0.062 | 45.5 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Official Snowball direct | `snowballDirect[NORWEGIAN_NYNORSK]` | 0.955 | 0.076 | 70.4 | 1.548 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[NORWEGIAN_NYNORSK]` | 1.352 | 0.106 | 99.7 | 2.191 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-
-
-
+| Radixor | `radixor[NORWEGIAN_NYNORSK]` | 0.584 | 0.057 | 43.1 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Official Snowball direct | `snowballDirect[NORWEGIAN_NYNORSK]` | 1.087 | 0.097 | 80.2 | 1.861 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[NORWEGIAN_NYNORSK]` | 1.256 | 0.095 | 92.6 | 2.149 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -312,7 +306,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `NN_NO`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/persian.md
+++ b/docs/benchmarks/languages/persian.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `fa-ir-default` | `1.0.0` | `FA_IR` | 69 | 3,770 | 138 | 3,632 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `fa-ir-default` | `1.0.0` | `FA_IR` | 69 | 3,770 | 138 | 3,632 | 5,000 |

 ## Radixor Patch Command Distribution

@@ -28,11 +28,9 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 95.836% | 95.677% | 100.000% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 95.836% | 95.677% | 100.000% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene PersianStemFilter | 1.485% | 0.000% | 40.580% | Lucene Persian suffix stemmer with required normalization in the measured path. |
-
-
-
+| Official Snowball direct | 3.660% | 0.000% | 100.000% | Official Snowball 3.1.0 generated Java stemmer; rule-based suffix algorithm. |

 ## Speed

@@ -40,15 +38,13 @@ Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 i

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `persianRadixor` | 0.243 | 0.004 | 66.9 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene PersianStemFilter | `persianLucenePersianStemFilter` | 0.469 | 0.007 | 129.1 | 1.930 | Persian suffix stemmer with Lucene normalization in the measured path. |
-
-
-
+| Radixor | `persianRadixor` | 0.230 | 0.003 | 46.0 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene PersianStemFilter | `persianLucenePersianStemFilter` | 0.448 | 0.009 | 89.5 | 1.948 | Persian suffix stemmer with Lucene normalization in the measured path. |
+| Official Snowball direct | `snowballDirect[PERSIAN]` | 1.490 | 0.055 | 298.1 | 6.486 | Official Snowball 3.1.0 generated Java stemmer; direct API. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -66,11 +62,11 @@ Runtime performance and linguistic grouping quality are independent dimensions.

 The default model is `fa-ir-default`, loaded from classpath resource `org/egothor/stemmer/models/fa-ir-default/stemmer.gz`. The following findings compare only deterministic `PRIMARY_OUTPUT` rows over identical included groups; candidate policies are reported separately as capability analyses.

- **ALL_WORDS:** `Radixor` ranks first by balanced accuracy at **0.976360** among 2 deterministic stemmers. The runner-up is `PERSIAN LUCENE PERSIAN STEM FILTER` at 0.502212, a difference of 0.474148. This rank does not imply leadership in throughput or every secondary metric.
- **LOWERCASE_GROUPS_ONLY:** `Radixor` ranks first by balanced accuracy at **0.976360** among 2 deterministic stemmers. The runner-up is `PERSIAN LUCENE PERSIAN STEM FILTER` at 0.502212, a difference of 0.474148. This rank does not imply leadership in throughput or every secondary metric.
+- **ALL_WORDS:** `Radixor` ranks first by balanced accuracy at **0.976360** among 3 deterministic stemmers. The runner-up is `SNOWBALL PERSIAN DIRECT` at 0.535123, a difference of 0.441236. This rank does not imply leadership in throughput or every secondary metric.
+- **LOWERCASE_GROUPS_ONLY:** `Radixor` ranks first by balanced accuracy at **0.976360** among 3 deterministic stemmers. The runner-up is `SNOWBALL PERSIAN DIRECT` at 0.535123, a difference of 0.441236. This rank does not imply leadership in throughput or every secondary metric.
 ### `ALL_WORDS`

-This mode contains **4 result rows**, **2 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.
+This mode contains **5 result rows**, **3 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.

 #### `PRIMARY_OUTPUT` ranking

@@ -79,7 +75,8 @@ This mode contains **4 result rows**, **2 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Balanced accuracy | Over-stemming (OI) | Under-stemming (UI) |
 |---:|---|---:|---:|---:|
 |1|Radixor|0.976360|0.000000%|4.728041%|
-|2|PERSIAN LUCENE PERSIAN STEM FILTER|0.502212|0.000049%|99.557494%|
+|2|SNOWBALL PERSIAN DIRECT|0.535123|0.001278%|92.974054%|
+|3|PERSIAN LUCENE PERSIAN STEM FILTER|0.502212|0.000049%|99.557494%|

 </div>

@@ -88,7 +85,8 @@ This mode contains **4 result rows**, **2 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | Precision | Recall | Specificity | Balanced accuracy | Pairwise accuracy | Error rate |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|1.000000|0.952720|1.000000|0.976360|0.999277|0.000723|
-|2|PERSIAN LUCENE PERSIAN STEM FILTER|PRIMARY_OUTPUT|0.992991|0.004425|1.000000|0.502212|0.984769|0.015231|
+|2|SNOWBALL PERSIAN DIRECT|PRIMARY_OUTPUT|0.988428|0.070259|0.999987|0.535123|0.985764|0.014236|
+|3|PERSIAN LUCENE PERSIAN STEM FILTER|PRIMARY_OUTPUT|0.992991|0.004425|1.000000|0.502212|0.984769|0.015231|

 </details>

@@ -97,7 +95,8 @@ This mode contains **4 result rows**, **2 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | F0.5 | F1 | F2 | Jaccard | Fowlkes–Mallows | MCC |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|0.990172|0.975787|0.961815|0.952720|0.976074|0.975715|
-|2|PERSIAN LUCENE PERSIAN STEM FILTER|PRIMARY_OUTPUT|0.021738|0.008811|0.005525|0.004425|0.066288|0.065774|
+|2|SNOWBALL PERSIAN DIRECT|PRIMARY_OUTPUT|0.273526|0.131193|0.086291|0.070202|0.263527|0.261598|
+|3|PERSIAN LUCENE PERSIAN STEM FILTER|PRIMARY_OUTPUT|0.021738|0.008811|0.005525|0.004425|0.066288|0.065774|

 </details>

@@ -106,7 +105,8 @@ This mode contains **4 result rows**, **2 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | TP | FP | FN | TN | Over error / possible | Under error / possible |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|91503|0|4541|6182152|0 / 6182152|4541 / 96044|
-|2|PERSIAN LUCENE PERSIAN STEM FILTER|PRIMARY_OUTPUT|425|3|95619|6182149|3 / 6182152|95619 / 96044|
+|2|SNOWBALL PERSIAN DIRECT|PRIMARY_OUTPUT|6748|79|89296|6182073|79 / 6182152|89296 / 96044|
+|3|PERSIAN LUCENE PERSIAN STEM FILTER|PRIMARY_OUTPUT|425|3|95619|6182149|3 / 6182152|95619 / 96044|

 </details>

@@ -174,7 +174,7 @@ Alternative candidates are capability analyses, not replacements for the determi

 ### `LOWERCASE_GROUPS_ONLY`

-This mode contains **4 result rows**, **2 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.
+This mode contains **5 result rows**, **3 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.

 #### `PRIMARY_OUTPUT` ranking

@@ -183,7 +183,8 @@ This mode contains **4 result rows**, **2 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Balanced accuracy | Over-stemming (OI) | Under-stemming (UI) |
 |---:|---|---:|---:|---:|
 |1|Radixor|0.976360|0.000000%|4.728041%|
-|2|PERSIAN LUCENE PERSIAN STEM FILTER|0.502212|0.000049%|99.557494%|
+|2|SNOWBALL PERSIAN DIRECT|0.535123|0.001278%|92.974054%|
+|3|PERSIAN LUCENE PERSIAN STEM FILTER|0.502212|0.000049%|99.557494%|

 </div>

@@ -192,7 +193,8 @@ This mode contains **4 result rows**, **2 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | Precision | Recall | Specificity | Balanced accuracy | Pairwise accuracy | Error rate |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|1.000000|0.952720|1.000000|0.976360|0.999277|0.000723|
-|2|PERSIAN LUCENE PERSIAN STEM FILTER|PRIMARY_OUTPUT|0.992991|0.004425|1.000000|0.502212|0.984769|0.015231|
+|2|SNOWBALL PERSIAN DIRECT|PRIMARY_OUTPUT|0.988428|0.070259|0.999987|0.535123|0.985764|0.014236|
+|3|PERSIAN LUCENE PERSIAN STEM FILTER|PRIMARY_OUTPUT|0.992991|0.004425|1.000000|0.502212|0.984769|0.015231|

 </details>

@@ -201,7 +203,8 @@ This mode contains **4 result rows**, **2 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | F0.5 | F1 | F2 | Jaccard | Fowlkes–Mallows | MCC |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|0.990172|0.975787|0.961815|0.952720|0.976074|0.975715|
-|2|PERSIAN LUCENE PERSIAN STEM FILTER|PRIMARY_OUTPUT|0.021738|0.008811|0.005525|0.004425|0.066288|0.065774|
+|2|SNOWBALL PERSIAN DIRECT|PRIMARY_OUTPUT|0.273526|0.131193|0.086291|0.070202|0.263527|0.261598|
+|3|PERSIAN LUCENE PERSIAN STEM FILTER|PRIMARY_OUTPUT|0.021738|0.008811|0.005525|0.004425|0.066288|0.065774|

 </details>

@@ -210,7 +213,8 @@ This mode contains **4 result rows**, **2 evaluated stemmers**, and **3 output p
 | Rank | Stemmer | Output policy | TP | FP | FN | TN | Over error / possible | Under error / possible |
 |---:|---|---|---:|---:|---:|---:|---:|---:|
 |1|Radixor|PRIMARY_OUTPUT|91503|0|4541|6182152|0 / 6182152|4541 / 96044|
-|2|PERSIAN LUCENE PERSIAN STEM FILTER|PRIMARY_OUTPUT|425|3|95619|6182149|3 / 6182152|95619 / 96044|
+|2|SNOWBALL PERSIAN DIRECT|PRIMARY_OUTPUT|6748|79|89296|6182073|79 / 6182152|89296 / 96044|
+|3|PERSIAN LUCENE PERSIAN STEM FILTER|PRIMARY_OUTPUT|425|3|95619|6182149|3 / 6182152|95619 / 96044|

 </details>

@@ -300,7 +304,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `FA_IR`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/polish.md
+++ b/docs/benchmarks/languages/polish.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `pl-pl-unimorph` | `1.0.0` | `PL_PL` | 9,990 | 132,308 | 19,957 | 112,351 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `pl-pl-unimorph` | `1.0.0` | `PL_PL` | 9,990 | 132,308 | 19,957 | 112,351 | 112,351 |

 ## Radixor Patch Command Distribution

@@ -30,14 +30,12 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 98.837% | 98.744% | 99.359% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 98.837% | 98.744% | 99.359% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene HunspellStemFilter | 89.545% | 88.272% | 96.713% | Benchmark-only Polish Hunspell dictionary compared via Lucene HunspellStemFilter. |
 | Lucene MorfologikFilter | 87.729% | 86.606% | 94.047% | Dictionary-based path; Morfologik can emit multiple terms. |
 | Lucene StempelFilter | 70.009% | 69.262% | 74.220% | Lucene TokenFilter integration path for table-driven Polish Stempel. |
 | Lucene StempelStemmer direct | 70.009% | 69.262% | 74.220% | Direct table-driven Polish Stempel stemmer API. |
-
-
-
+| Official Snowball direct | 22.315% | 20.225% | 34.078% | Official Snowball 3.1.0 generated Java stemmer; rule-based suffix algorithm. |

 ## Speed

@@ -45,18 +43,16 @@ Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 i

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `polishRadixor` | 8.972 | 0.203 | 79.9 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 524.081 | 35.121 | 4664.7 | 58.412 | Benchmark-only Polish Hunspell dictionary compared via Lucene HunspellStemFilter. |
-| Lucene StempelStemmer direct | `polishLuceneStempelStemmerDirect` | 37.947 | 0.335 | 337.8 | 4.229 | Direct table-driven Polish Stempel stemmer API. |
-| Lucene StempelFilter | `polishLuceneStempelFilter` | 43.090 | 0.411 | 383.5 | 4.803 | Lucene TokenFilter integration path for table-driven Polish Stempel. |
-| Lucene MorfologikFilter | `polishLuceneMorfologikFilter` | 143.527 | 1.176 | 1277.5 | 15.997 | Dictionary-based Morfologik TokenFilter; may emit multiple terms. |
-
-
-
+| Radixor | `polishRadixor` | 8.122 | 0.146 | 72.3 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 471.669 | 26.993 | 4198.2 | 58.070 | Benchmark-only Polish Hunspell dictionary compared via Lucene HunspellStemFilter. |
+| Lucene StempelStemmer direct | `polishLuceneStempelStemmerDirect` | 31.524 | 0.189 | 280.6 | 3.881 | Direct table-driven Polish Stempel stemmer API. |
+| Lucene StempelFilter | `polishLuceneStempelFilter` | 39.180 | 0.362 | 348.7 | 4.824 | Lucene TokenFilter integration path for table-driven Polish Stempel. |
+| Lucene MorfologikFilter | `polishLuceneMorfologikFilter` | 138.971 | 1.429 | 1236.9 | 17.110 | Dictionary-based Morfologik TokenFilter; may emit multiple terms. |
+| Official Snowball direct | `snowballDirect[POLISH]` | 9.715 | 0.858 | 86.5 | 1.196 | Official Snowball 3.1.0 generated Java stemmer; direct API. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -74,11 +70,11 @@ Runtime performance and linguistic grouping quality are independent dimensions.

 The default model is `pl-pl-unimorph`, loaded from classpath resource `org/egothor/stemmer/models/pl-pl-unimorph/stemmer.gz`. The following findings compare only deterministic `PRIMARY_OUTPUT` rows over identical included groups; candidate policies are reported separately as capability analyses.

- **ALL_WORDS:** `Radixor` ranks first by balanced accuracy at **0.991105** among 5 deterministic stemmers. The runner-up is `POLISH LUCENE MORFOLOGIK FILTER` at 0.948392, a difference of 0.042713. This rank does not imply leadership in throughput or every secondary metric.
- **LOWERCASE_GROUPS_ONLY:** `Radixor` ranks first by balanced accuracy at **0.991301** among 5 deterministic stemmers. The runner-up is `POLISH LUCENE MORFOLOGIK FILTER` at 0.948417, a difference of 0.042884. This rank does not imply leadership in throughput or every secondary metric.
+- **ALL_WORDS:** `Radixor` ranks first by balanced accuracy at **0.991105** among 6 deterministic stemmers. The runner-up is `POLISH LUCENE MORFOLOGIK FILTER` at 0.948392, a difference of 0.042713. This rank does not imply leadership in throughput or every secondary metric.
+- **LOWERCASE_GROUPS_ONLY:** `Radixor` ranks first by balanced accuracy at **0.991301** among 6 deterministic stemmers. The runner-up is `POLISH LUCENE MORFOLOGIK FILTER` at 0.948417, a difference of 0.042884. This rank does not imply leadership in throughput or every secondary metric.
 ### `ALL_WORDS`

-This mode contains **11 result rows**, **5 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.
+This mode contains **12 result rows**, **6 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.

 #### `PRIMARY_OUTPUT` ranking

@@ -91,6 +87,7 @@ This mode contains **11 result rows**, **5 evaluated stemmers**, and **3 output
 |3|HUNSPELL POLISH LUCENE FILTER|0.933457|0.000383%|13.308172%|
 |4|POLISH LUCENE STEMPEL DIRECT|0.855699|0.000602%|28.859618%|
 |5|POLISH LUCENE STEMPEL FILTER|0.855699|0.000602%|28.859618%|
+|6|SNOWBALL POLISH DIRECT|0.823625|0.000967%|35.273970%|

 </div>

@@ -103,6 +100,7 @@ This mode contains **11 result rows**, **5 evaluated stemmers**, and **3 output
 |3|HUNSPELL POLISH LUCENE FILTER|PRIMARY_OUTPUT|0.971931|0.866918|0.999996|0.933457|0.999976|0.000024|
 |4|POLISH LUCENE STEMPEL DIRECT|PRIMARY_OUTPUT|0.947549|0.711404|0.999994|0.855699|0.999950|0.000050|
 |5|POLISH LUCENE STEMPEL FILTER|PRIMARY_OUTPUT|0.947549|0.711404|0.999994|0.855699|0.999950|0.000050|
+|6|SNOWBALL POLISH DIRECT|PRIMARY_OUTPUT|0.910978|0.647260|0.999990|0.823625|0.999936|0.000064|

 </details>

@@ -115,6 +113,7 @@ This mode contains **11 result rows**, **5 evaluated stemmers**, and **3 output
 |3|HUNSPELL POLISH LUCENE FILTER|PRIMARY_OUTPUT|0.948942|0.916426|0.886065|0.845744|0.917924|0.917913|
 |4|POLISH LUCENE STEMPEL DIRECT|PRIMARY_OUTPUT|0.888559|0.812669|0.748723|0.684450|0.821030|0.821007|
 |5|POLISH LUCENE STEMPEL FILTER|PRIMARY_OUTPUT|0.888559|0.812669|0.748723|0.684450|0.821030|0.821007|
+|6|SNOWBALL POLISH DIRECT|PRIMARY_OUTPUT|0.842338|0.756803|0.687038|0.608756|0.767880|0.767852|

 </details>

@@ -127,6 +126,7 @@ This mode contains **11 result rows**, **5 evaluated stemmers**, and **3 output
 |3|HUNSPELL POLISH LUCENE FILTER|PRIMARY_OUTPUT|968411|27967|148662|7303210371|27967 / 7303238338|148662 / 1117073|
 |4|POLISH LUCENE STEMPEL DIRECT|PRIMARY_OUTPUT|794690|43990|322383|7303194348|43990 / 7303238338|322383 / 1117073|
 |5|POLISH LUCENE STEMPEL FILTER|PRIMARY_OUTPUT|794690|43990|322383|7303194348|43990 / 7303238338|322383 / 1117073|
+|6|SNOWBALL POLISH DIRECT|PRIMARY_OUTPUT|723037|70656|394036|7303167682|70656 / 7303238338|394036 / 1117073|

 </details>

@@ -208,7 +208,7 @@ Alternative candidates are capability analyses, not replacements for the determi

 ### `LOWERCASE_GROUPS_ONLY`

-This mode contains **11 result rows**, **5 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.
+This mode contains **12 result rows**, **6 evaluated stemmers**, and **3 output policies**. Applied-row and form counts are shown per row because adapters share the language corpus but policy rows remain independently auditable. `PRIMARY_OUTPUT` and `ALL_CANDIDATES` rankings are ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. `ANY_CANDIDATE` has no single rank metric and is listed alphabetically. Balanced accuracy is a navigation metric, not a universally authoritative quality score.

 #### `PRIMARY_OUTPUT` ranking

@@ -221,6 +221,7 @@ This mode contains **11 result rows**, **5 evaluated stemmers**, and **3 output
 |3|HUNSPELL POLISH LUCENE FILTER|0.933546|0.000382%|13.290396%|
 |4|POLISH LUCENE STEMPEL DIRECT|0.856335|0.000611%|28.732387%|
 |5|POLISH LUCENE STEMPEL FILTER|0.856335|0.000611%|28.732387%|
+|6|SNOWBALL POLISH DIRECT|0.823465|0.000990%|35.306102%|

 </div>

@@ -233,6 +234,7 @@ This mode contains **11 result rows**, **5 evaluated stemmers**, and **3 output
 |3|HUNSPELL POLISH LUCENE FILTER|PRIMARY_OUTPUT|0.972469|0.867096|0.999996|0.933546|0.999975|0.000025|
 |4|POLISH LUCENE STEMPEL DIRECT|PRIMARY_OUTPUT|0.947796|0.712676|0.999994|0.856335|0.999949|0.000051|
 |5|POLISH LUCENE STEMPEL FILTER|PRIMARY_OUTPUT|0.947796|0.712676|0.999994|0.856335|0.999949|0.000051|
+|6|SNOWBALL POLISH DIRECT|PRIMARY_OUTPUT|0.910487|0.646939|0.999990|0.823465|0.999935|0.000065|

 </details>

@@ -245,6 +247,7 @@ This mode contains **11 result rows**, **5 evaluated stemmers**, and **3 output
 |3|HUNSPELL POLISH LUCENE FILTER|PRIMARY_OUTPUT|0.949394|0.916764|0.886303|0.846320|0.918272|0.918260|
 |4|POLISH LUCENE STEMPEL DIRECT|PRIMARY_OUTPUT|0.889130|0.813590|0.749881|0.685758|0.821871|0.821848|
 |5|POLISH LUCENE STEMPEL FILTER|PRIMARY_OUTPUT|0.889130|0.813590|0.749881|0.685758|0.821871|0.821848|
+|6|SNOWBALL POLISH DIRECT|PRIMARY_OUTPUT|0.841894|0.756414|0.686693|0.608253|0.767483|0.767454|

 </details>

@@ -257,6 +260,7 @@ This mode contains **11 result rows**, **5 evaluated stemmers**, and **3 output
 |3|HUNSPELL POLISH LUCENE FILTER|PRIMARY_OUTPUT|963133|27267|147624|7133072951|27267 / 7133100218|147624 / 1110757|
 |4|POLISH LUCENE STEMPEL DIRECT|PRIMARY_OUTPUT|791610|43601|319147|7133056617|43601 / 7133100218|319147 / 1110757|
 |5|POLISH LUCENE STEMPEL FILTER|PRIMARY_OUTPUT|791610|43601|319147|7133056617|43601 / 7133100218|319147 / 1110757|
+|6|SNOWBALL POLISH DIRECT|PRIMARY_OUTPUT|718592|70647|392165|7133029571|70647 / 7133100218|392165 / 1110757|

 </details>

@@ -360,7 +364,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `PL_PL`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/portuguese.md
+++ b/docs/benchmarks/languages/portuguese.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `pt-pt-default` | `1.0.0` | `PT_PT` | 4,001 | 215,490 | 8,002 | 207,488 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `pt-pt-default` | `1.0.0` | `PT_PT` | 4,001 | 215,490 | 8,002 | 207,488 | 207,488 |

 ## Radixor Patch Command Distribution

@@ -30,35 +30,29 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 99.815% | 99.808% | 100.000% | Full Radixor dictionary patch-command stemmer. |
-| Lucene PortugueseLightStemFilter | 8.966% | 5.558% | 97.326% | Light suffix stemmer; intentionally narrower than a dictionary-derived stemmer. |
+| Radixor | 99.815% | 99.808% | 100.000% | Radixor dictionary-trained patch-command stemmer. |
+| Lucene PortugueseLightStemFilter | 8.966% | 5.558% | 97.326% | Light suffix stemmer; intentionally narrower than Radixor's dictionary-trained transformation model. |
 | Lucene PortugueseMinimalStemFilter | 5.539% | 1.896% | 100.000% | Minimal suffix reducer; narrow baseline, not a full stemmer. |
 | Lucene SnowballFilter | 0.625% | 0.558% | 2.374% | Lucene TokenFilter integration path around the Snowball algorithm. |
 | Official Snowball direct | 0.625% | 0.558% | 2.374% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
 | Lucene PortugueseStemFilter | 0.312% | 0.308% | 0.425% | Portuguese RSLP-style Lucene TokenFilter stemmer. |

-
-
-
 ## Speed

 Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 independent forks, and 1 thread. Relative factor is computed against the single Radixor row on this language page. Values below 1.000 are faster than that Radixor baseline; values above 1.000 are slower.

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `portugueseRadixor` | 12.301 | 0.252 | 59.3 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene PortugueseLightStemFilter | `portugueseLucenePortugueseLightStemFilter` | 11.409 | 0.151 | 55.0 | 0.927 | Light Portuguese suffix stemmer. |
-| Lucene PortugueseMinimalStemFilter | `portugueseLucenePortugueseMinimalStemFilter` | 15.619 | 0.084 | 75.3 | 1.270 | Minimal Portuguese suffix reducer. |
-| Official Snowball direct | `snowballDirect[PORTUGUESE]` | 57.577 | 1.591 | 277.5 | 4.681 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[PORTUGUESE]` | 63.403 | 2.720 | 305.6 | 5.154 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-| Lucene PortugueseStemFilter | `portugueseLucenePortugueseStemFilter` | 158.014 | 5.150 | 761.6 | 12.845 | Portuguese RSLP-style Lucene TokenFilter. |
-
-
-
+| Radixor | `portugueseRadixor` | 10.902 | 0.166 | 52.5 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene PortugueseLightStemFilter | `portugueseLucenePortugueseLightStemFilter` | 10.125 | 0.161 | 48.8 | 0.929 | Light Portuguese suffix stemmer. |
+| Lucene PortugueseMinimalStemFilter | `portugueseLucenePortugueseMinimalStemFilter` | 14.338 | 0.156 | 69.1 | 1.315 | Minimal Portuguese suffix reducer. |
+| Official Snowball direct | `snowballDirect[PORTUGUESE]` | 52.193 | 1.905 | 251.5 | 4.788 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[PORTUGUESE]` | 58.991 | 2.457 | 284.3 | 5.411 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
+| Lucene PortugueseStemFilter | `portugueseLucenePortugueseStemFilter` | 164.457 | 8.688 | 792.6 | 15.085 | Portuguese RSLP-style Lucene TokenFilter. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -342,7 +336,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `PT_PT`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/russian.md
+++ b/docs/benchmarks/languages/russian.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `ru-ru-default` | `1.0.0` | `RU_RU` | 37,410 | 806,279 | 74,808 | 731,471 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `ru-ru-default` | `1.0.0` | `RU_RU` | 37,410 | 806,279 | 74,808 | 731,471 | 731,471 |

 ## Radixor Patch Command Distribution

@@ -30,31 +30,25 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 98.807% | 98.696% | 99.896% | Full Radixor dictionary patch-command stemmer. |
-| Lucene RussianLightStemFilter | 9.658% | 8.452% | 21.447% | Light suffix stemmer; intentionally narrower than a dictionary-derived stemmer. |
+| Radixor | 98.807% | 98.696% | 99.896% | Radixor dictionary-trained patch-command stemmer. |
+| Lucene RussianLightStemFilter | 9.658% | 8.452% | 21.447% | Light suffix stemmer; intentionally narrower than Radixor's dictionary-trained transformation model. |
 | Lucene SnowballFilter | 9.162% | 8.162% | 18.936% | Lucene TokenFilter integration path around the Snowball algorithm. |
 | Official Snowball direct | 9.162% | 8.162% | 18.936% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |

-
-
-
 ## Speed

 Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 independent forks, and 1 thread. Relative factor is computed against the single Radixor row on this language page. Values below 1.000 are faster than that Radixor baseline; values above 1.000 are slower.

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `russianRadixor` | 90.151 | 1.796 | 123.2 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene RussianLightStemFilter | `russianLuceneRussianLightStemFilter` | 59.456 | 2.102 | 81.3 | 0.660 | Light Russian suffix stemmer. |
-| Official Snowball direct | `snowballDirect[RUSSIAN]` | 102.353 | 1.669 | 139.9 | 1.135 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[RUSSIAN]` | 138.597 | 4.727 | 189.5 | 1.537 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-
-
-
+| Radixor | `russianRadixor` | 72.723 | 1.809 | 99.4 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene RussianLightStemFilter | `russianLuceneRussianLightStemFilter` | 58.844 | 3.217 | 80.4 | 0.809 | Light Russian suffix stemmer. |
+| Official Snowball direct | `snowballDirect[RUSSIAN]` | 103.471 | 8.136 | 141.5 | 1.423 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[RUSSIAN]` | 130.783 | 3.979 | 178.8 | 1.798 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -322,7 +316,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `RU_RU`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/spanish.md
+++ b/docs/benchmarks/languages/spanish.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `es-es-default` | `1.0.0` | `ES_ES` | 65,059 | 926,393 | 120,121 | 806,272 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `es-es-default` | `1.0.0` | `ES_ES` | 65,059 | 926,393 | 120,121 | 806,272 | 806,272 |

 ## Radixor Patch Command Distribution

@@ -30,37 +30,31 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 97.459% | 97.544% | 96.891% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 97.459% | 97.544% | 96.891% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene HunspellStemFilter | 49.074% | 42.656% | 92.154% | Benchmark-only Spanish Hunspell dictionary compared via Lucene HunspellStemFilter. |
 | Lucene SpanishMinimalStemFilter | 17.284% | 5.347% | 97.403% | Minimal suffix reducer; narrow baseline, not a full stemmer. |
 | Lucene SpanishPluralStemFilter | 15.140% | 5.802% | 77.820% | Plural-focused suffix reducer; narrow baseline. |
-| Lucene SpanishLightStemFilter | 9.577% | 7.088% | 26.279% | Light suffix stemmer; intentionally narrower than a dictionary-derived stemmer. |
+| Lucene SpanishLightStemFilter | 9.577% | 7.088% | 26.279% | Light suffix stemmer; intentionally narrower than Radixor's dictionary-trained transformation model. |
 | Lucene SnowballFilter | 4.889% | 4.287% | 8.932% | Lucene TokenFilter integration path around the Snowball algorithm. |
 | Official Snowball direct | 4.889% | 4.287% | 8.930% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |

-
-
-
 ## Speed

 Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 independent forks, and 1 thread. Relative factor is computed against the single Radixor row on this language page. Values below 1.000 are faster than that Radixor baseline; values above 1.000 are slower.

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `spanishRadixor` | 81.605 | 1.347 | 101.2 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 2033.430 | 14.863 | 2522.0 | 24.918 | Benchmark-only Spanish Hunspell dictionary compared via Lucene HunspellStemFilter. |
-| Lucene SpanishMinimalStemFilter | `spanishLuceneSpanishMinimalStemFilter` | 42.144 | 1.556 | 52.3 | 0.516 | Minimal Spanish suffix reducer; narrow baseline. |
-| Lucene SpanishLightStemFilter | `spanishLuceneSpanishLightStemFilter` | 44.479 | 1.291 | 55.2 | 0.545 | Light Spanish suffix stemmer. |
-| Lucene SpanishPluralStemFilter | `spanishLuceneSpanishPluralStemFilter` | 96.537 | 3.418 | 119.7 | 1.183 | Plural-oriented Spanish suffix reducer. |
-| Official Snowball direct | `snowballDirect[SPANISH]` | 172.151 | 7.261 | 213.5 | 2.110 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[SPANISH]` | 201.697 | 9.363 | 250.2 | 2.472 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-
-
-
+| Radixor | `spanishRadixor` | 63.164 | 1.885 | 78.3 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 1936.800 | 18.685 | 2402.2 | 30.663 | Benchmark-only Spanish Hunspell dictionary compared via Lucene HunspellStemFilter. |
+| Lucene SpanishMinimalStemFilter | `spanishLuceneSpanishMinimalStemFilter` | 40.414 | 1.475 | 50.1 | 0.640 | Minimal Spanish suffix reducer; narrow baseline. |
+| Lucene SpanishLightStemFilter | `spanishLuceneSpanishLightStemFilter` | 43.922 | 1.497 | 54.5 | 0.695 | Light Spanish suffix stemmer. |
+| Lucene SpanishPluralStemFilter | `spanishLuceneSpanishPluralStemFilter` | 89.799 | 3.474 | 111.4 | 1.422 | Plural-oriented Spanish suffix reducer. |
+| Official Snowball direct | `snowballDirect[SPANISH]` | 192.868 | 11.684 | 239.2 | 3.053 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[SPANISH]` | 182.719 | 6.957 | 226.6 | 2.893 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -366,7 +360,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `ES_ES`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/swedish.md
+++ b/docs/benchmarks/languages/swedish.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `sv-se-default` | `1.0.0` | `SV_SE` | 12,371 | 110,468 | 24,731 | 85,737 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `sv-se-default` | `1.0.0` | `SV_SE` | 12,371 | 110,468 | 24,731 | 85,737 | 85,737 |

 ## Radixor Patch Command Distribution

@@ -30,33 +30,27 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 96.713% | 97.407% | 94.307% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 96.713% | 97.407% | 94.307% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene SwedishMinimalStemFilter | 49.532% | 49.186% | 50.730% | Minimal suffix reducer; narrow baseline, not a full stemmer. |
-| Lucene SwedishLightStemFilter | 45.672% | 46.383% | 43.209% | Light suffix stemmer; intentionally narrower than a dictionary-derived stemmer. |
+| Lucene SwedishLightStemFilter | 45.672% | 46.383% | 43.209% | Light suffix stemmer; intentionally narrower than Radixor's dictionary-trained transformation model. |
 | Official Snowball direct | 40.068% | 37.512% | 48.926% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |
 | Lucene SnowballFilter | 38.785% | 35.839% | 48.999% | Lucene TokenFilter integration path around the Snowball algorithm. |

-
-
-
 ## Speed

 Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 independent forks, and 1 thread. Relative factor is computed against the single Radixor row on this language page. Values below 1.000 are faster than that Radixor baseline; values above 1.000 are slower.

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `swedishRadixor` | 5.476 | 0.081 | 63.9 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene SwedishMinimalStemFilter | `swedishLuceneSwedishMinimalStemFilter` | 4.741 | 0.086 | 55.3 | 0.866 | Minimal Swedish suffix reducer. |
-| Lucene SwedishLightStemFilter | `swedishLuceneSwedishLightStemFilter` | 4.893 | 0.053 | 57.1 | 0.893 | Light Swedish suffix stemmer. |
-| Official Snowball direct | `snowballDirect[SWEDISH]` | 7.606 | 0.555 | 88.7 | 1.389 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[SWEDISH]` | 10.295 | 0.749 | 120.1 | 1.880 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-
-
-
+| Radixor | `swedishRadixor` | 5.078 | 0.104 | 59.2 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene SwedishMinimalStemFilter | `swedishLuceneSwedishMinimalStemFilter` | 4.417 | 0.061 | 51.5 | 0.870 | Minimal Swedish suffix reducer. |
+| Lucene SwedishLightStemFilter | `swedishLuceneSwedishLightStemFilter` | 5.090 | 0.373 | 59.4 | 1.002 | Light Swedish suffix stemmer. |
+| Official Snowball direct | `snowballDirect[SWEDISH]` | 7.497 | 0.653 | 87.4 | 1.476 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[SWEDISH]` | 9.831 | 0.648 | 114.7 | 1.936 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -332,7 +326,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `SV_SE`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/ukrainian.md
+++ b/docs/benchmarks/languages/ukrainian.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `uk-ua-default` | `1.0.0` | `UK_UA` | 1,493 | 15,737 | 2,985 | 12,752 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `uk-ua-default` | `1.0.0` | `UK_UA` | 1,493 | 15,737 | 2,985 | 12,752 | 12,752 |

 ## Radixor Patch Command Distribution

@@ -30,31 +30,25 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 99.307% | 99.365% | 99.062% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 99.307% | 99.365% | 99.062% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene HunspellStemFilter | 86.815% | 83.759% | 99.866% | Benchmark-only Ukrainian Hunspell dictionary compared via Lucene HunspellStemFilter. |
 | Lucene MorfologikFilter | 92.362% | 90.637% | 99.732% | Dictionary-based path; Morfologik can emit multiple terms. |
 | Morfologik direct | 92.362% | 90.637% | 99.732% | Direct dictionary lookup; first returned stem is used for quality when no ranking weight is exposed. |

-
-
-
 ## Speed

 Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 independent forks, and 1 thread. Relative factor is computed against the single Radixor row on this language page. Values below 1.000 are faster than that Radixor baseline; values above 1.000 are slower.

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `ukrainianRadixor` | 0.639 | 0.009 | 50.1 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 47.919 | 5.308 | 3757.8 | 74.957 | Benchmark-only Ukrainian Hunspell dictionary compared via Lucene HunspellStemFilter. |
-| Morfologik direct | `ukrainianMorfologikDirect` | 8.662 | 0.105 | 679.3 | 13.550 | Direct Morfologik dictionary lookup; first returned stem is used for quality. |
-| Lucene MorfologikFilter | `ukrainianLuceneMorfologikFilter` | 15.367 | 0.219 | 1205.1 | 24.038 | Dictionary-based Morfologik TokenFilter; may emit multiple terms. |
-
-
-
+| Radixor | `ukrainianRadixor` | 0.594 | 0.010 | 46.6 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Lucene HunspellStemFilter | `luceneHunspellStemFilter` | 39.820 | 3.772 | 3122.6 | 67.067 | Benchmark-only Ukrainian Hunspell dictionary compared via Lucene HunspellStemFilter. |
+| Morfologik direct | `ukrainianMorfologikDirect` | 8.231 | 0.121 | 645.5 | 13.863 | Direct Morfologik dictionary lookup; first returned stem is used for quality. |
+| Lucene MorfologikFilter | `ukrainianLuceneMorfologikFilter` | 14.700 | 0.176 | 1152.8 | 24.758 | Dictionary-based Morfologik TokenFilter; may emit multiple terms. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -364,7 +358,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `UK_UA`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/languages/yiddish.md
+++ b/docs/benchmarks/languages/yiddish.md
@@ -8,9 +8,9 @@ Radixor must not be read as simply "slower" when a narrow competitor has a lower

 ## Dictionary Corpus

-| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed speed tokens |
-| --- | --- | --- | ---: | ---: | ---: | ---: |
-| `yi-default` | `1.0.0` | `YI` | 802 | 4,300 | 1,524 | 2,776 |
+| Model ID | Model version | Language | Dictionary rows | Complete quality tokens | Already-root tokens | Changed tokens | JMH timing tokens |
+| --- | --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `yi-default` | `1.0.0` | `YI` | 802 | 4,300 | 1,524 | 2,776 | 5,000 |

 ## Radixor Patch Command Distribution

@@ -29,29 +29,23 @@ Accuracy is computed from JMH auxiliary counters in the current report. The coun

 | Stemmer | All exact | Changed exact | Root preserved | Note |
 | --- | ---: | ---: | ---: | --- |
-| Radixor | 98.930% | 98.343% | 100.000% | Full Radixor dictionary patch-command stemmer. |
+| Radixor | 98.930% | 98.343% | 100.000% | Radixor dictionary-trained patch-command stemmer. |
 | Lucene SnowballFilter | 2.837% | 2.558% | 3.346% | Lucene TokenFilter integration path around the Snowball algorithm. |
 | Official Snowball direct | 2.837% | 2.558% | 3.346% | Official Snowball generated Java stemmer; rule-based suffix algorithm. |

-
-
-
 ## Speed

 Speed uses JMH average time, 5 warmup iterations, 10 measurement iterations, 3 independent forks, and 1 thread. Relative factor is computed against the single Radixor row on this language page. Values below 1.000 are faster than that Radixor baseline; values above 1.000 are slower.

 | Stemmer | Benchmark method | Score ms/op | Error ms | ns/token | Relative vs Radixor | Note |
 | --- | --- | ---: | ---: | ---: | ---: | --- |
-| Radixor | `radixor[YIDDISH]` | 0.249 | 0.001 | 89.6 | 1.000 | Full Radixor dictionary patch-command stemmer. |
-| Official Snowball direct | `snowballDirect[YIDDISH]` | 1.574 | 0.066 | 567.1 | 6.330 | Official Snowball generated Java stemmer; direct API. |
-| Lucene SnowballFilter | `luceneSnowballFilter[YIDDISH]` | 1.849 | 0.079 | 665.9 | 7.434 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |
-
-
-
+| Radixor | `radixor[YIDDISH]` | 0.234 | 0.001 | 46.8 | 1.000 | Radixor dictionary-trained patch-command stemmer. |
+| Official Snowball direct | `snowballDirect[YIDDISH]` | 1.487 | 0.062 | 297.5 | 6.354 | Official Snowball generated Java stemmer; direct API. |
+| Lucene SnowballFilter | `luceneSnowballFilter[YIDDISH]` | 1.754 | 0.070 | 350.8 | 7.492 | Lucene TokenFilter path around Snowball; includes TokenStream overhead. |

 ## Interpretation Notes

- Radixor is a dictionary-derived patch-command stemmer. Its quality depends on the language resource used to train the compiled trie.
+- Radixor is a dictionary-trained patch-command stemmer. Its learned transformations can generalize beyond the word forms listed in the training resource.
 - Light, minimal, plural, and possessive filters are narrow baselines. They can be fast because they intentionally perform less linguistic work.
 - Lucene TokenFilter rows include TokenStream, attribute, and required normalization overhead. Direct rows measure exposed direct APIs.
 - Morfologik rows are dictionary-based and can emit multiple terms for one input token. Quality rows use the first returned term when no ranking weight is available.
@@ -311,7 +305,7 @@ Standard ARI, homogeneity, completeness, V-measure, and NMI are not calculated:
 ### Provenance

 - Authoritative source: `docs/benchmarks/data/stemming-quality.csv`
- Source SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
+- Source SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
 - Evaluation command: `./gradlew stemmingQuality --no-daemon`
 - Dictionary language: `YI`
 - Processing modes: `ALL_WORDS`, `LOWERCASE_GROUPS_ONLY`
--- a/docs/benchmarks/reference/english-coverage.md
+++ b/docs/benchmarks/reference/english-coverage.md
@@ -6,16 +6,16 @@ This benchmark is the clearest demonstration of the Radixor quality/speed envelo

 | Used rows | Actual row ratio | All exact | Changed exact | Root preserved | Speed ms/op | Error ms | ns/token |
 | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
-| 100% | 100.000% | 97.478% | 97.197% | 97.552% | 20.627 | 2.117 | 98.0 |
-| 90% | 90.000% | 97.047% | 94.913% | 97.613% | 21.713 | 2.104 | 103.2 |
-| 80% | 80.000% | 96.635% | 92.768% | 97.661% | 17.408 | 1.438 | 82.7 |
-| 70% | 70.000% | 96.209% | 90.565% | 97.705% | 16.946 | 1.531 | 80.5 |
-| 60% | 60.000% | 95.750% | 88.384% | 97.703% | 15.735 | 1.278 | 74.8 |
-| 50% | 50.000% | 95.262% | 86.107% | 97.690% | 14.714 | 1.089 | 69.9 |
-| 40% | 40.000% | 94.753% | 83.855% | 97.643% | 15.090 | 1.254 | 71.7 |
-| 30% | 30.000% | 94.208% | 81.651% | 97.537% | 13.773 | 1.071 | 65.4 |
-| 20% | 20.000% | 93.633% | 79.366% | 97.416% | 15.396 | 2.497 | 73.1 |
-| 10% | 10.000% | 92.868% | 76.516% | 97.204% | 16.970 | 2.847 | 80.6 |
+| 100% | 100.000% | 97.478% | 97.197% | 97.552% | 15.064 | 0.658 | 71.6 |
+| 90% | 90.000% | 97.047% | 94.913% | 97.613% | 17.798 | 2.161 | 84.6 |
+| 80% | 80.000% | 96.635% | 92.768% | 97.661% | 13.900 | 0.941 | 66.0 |
+| 70% | 70.000% | 96.209% | 90.565% | 97.705% | 14.809 | 1.376 | 70.3 |
+| 60% | 60.000% | 95.750% | 88.384% | 97.703% | 13.186 | 0.930 | 62.6 |
+| 50% | 50.000% | 95.262% | 86.107% | 97.690% | 12.852 | 0.943 | 61.1 |
+| 40% | 40.000% | 94.753% | 83.855% | 97.643% | 12.358 | 0.831 | 58.7 |
+| 30% | 30.000% | 94.208% | 81.651% | 97.537% | 11.657 | 0.921 | 55.4 |
+| 20% | 20.000% | 93.633% | 79.366% | 97.416% | 11.494 | 1.256 | 54.6 |
+| 10% | 10.000% | 92.868% | 76.516% | 97.204% | 9.895 | 0.925 | 47.0 |

 ## Column Meanings

--- a/docs/benchmarks/reference/environment.md
+++ b/docs/benchmarks/reference/environment.md
@@ -4,25 +4,25 @@ The values below are environment-specific and must not be read as universal perf

 | Item | Value |
 | --- | --- |
-| Benchmark date | 2026-07-23 (Europe/Prague) |
+| Benchmark date | 2026-08-10 (Europe/Prague) |
 | Corpus command | `./gradlew benchmarkCorpusReport --no-daemon` |
-| Exact-root accuracy command | Direct JMH execution of the four `*BenchmarkQuality` classes selected in `stemmer-accuracy-2026-07-23.txt`; timing scores are discarded |
+| Exact-root accuracy command | `tools/run-published-accuracy-benchmarks.sh 2026-08-10`; all four `*BenchmarkQuality` classes are selected and timing scores are discarded |
 | Stemming-quality command | `./gradlew stemmingQuality --no-daemon` |
-| Published speed command | `tools/run-published-speed-benchmarks.sh 2026-07-23` |
-| Published speed run interval | 2026-07-23 12:58:50 to 15:15:43 Europe/Prague (2 h 16 min 53 s, including idle intervals and both JMH suites) |
+| Published speed command | `tools/run-published-speed-benchmarks.sh 2026-08-10` |
+| Published speed run interval | 2026-08-10 16:22:33 to 18:36:41 Europe/Prague (2 h 14 min 8 s, including idle intervals and both JMH suites) |
 | Stabilization intervals | 120 s before the main speed matrix; 60 s between the main matrix and coverage-speed suite |
 | Corpus and command report | `build/reports/jmh/benchmark-corpora.csv` |
-| Exact-root reports | `build/reports/jmh/stemmer-accuracy-2026-07-23.csv` and `.txt` |
-| Speed reports | `build/reports/jmh/stemmer-speed-2026-07-23.csv` and `.txt` |
-| English coverage accuracy reports | `build/reports/jmh/english-coverage-accuracy-2026-07-23.csv` and `.txt` |
-| English coverage speed reports | `build/reports/jmh/english-coverage-speed-2026-07-23.csv` and `.txt` |
+| Exact-root reports | `build/reports/jmh/stemmer-accuracy-2026-08-10.csv` and `.txt` |
+| Speed reports | `build/reports/jmh/stemmer-speed-2026-08-10.csv` and `.txt` |
+| English coverage accuracy reports | `build/reports/jmh/english-coverage-accuracy-2026-08-10.csv` and `.txt` |
+| English coverage speed reports | `build/reports/jmh/english-coverage-speed-2026-08-10.csv` and `.txt` |
 | Stemming-quality reports | `build/reports/stemming-quality/stemming-quality.csv` and `.md` |
-| Environment report | `build/reports/jmh/performance-environment-2026-07-23.txt` |
-| Selected speed methods | `build/reports/jmh/published-speed-benchmarks-2026-07-23.txt` |
+| Environment report | `build/reports/jmh/performance-environment-2026-08-10.txt` |
+| Selected speed methods | `build/reports/jmh/published-speed-benchmarks-2026-08-10.txt` |
 | Comparison scope | Same-language methods used by the 20 language pages; `PolishPolimorfStemmerComparisonBenchmark`, all quality methods, the separate CISTEM gold-standard experiment, and internal trie microbenchmarks are excluded |
 | Model scope | Exactly the 20 IDs declared by `Language.defaultModelId()`; Polish uses `pl-pl-unimorph`, and `pl-pl-polimorf` is not measured |
-| Core base commit | `1f1b03c6a8d36a0918b92ebde698e5379a2a5946` |
-| Measured source state | `release@4.0.0-dirty`; exact tracked changes and untracked-source checksums are retained as `measured-source-2026-07-23.patch` and `measured-untracked-2026-07-23.sha256` |
+| Core base commit | `b45e143c8484c2ae1d6e31069a2e67232c4f7f29` |
+| Measured source state | `release@4.1.0-dirty`; exact tracked changes and untracked-source checksums are retained as `measured-source-2026-08-10.patch` and `measured-untracked-2026-08-10.sha256` |
 | JMH version | 1.37 |
 | Speed benchmark mode | Average time, `time/op` |
 | Score unit | `ns/op`; language pages additionally derive `ms/op` and `ns/token` |
@@ -32,21 +32,21 @@ The values below are environment-specific and must not be read as universal perf
 | Speed threads | 1 |
 | Speed fork heap | Fixed `-Xms6g -Xmx6g` |
 | Reported uncertainty | JMH `Score Error (99.9%)` over 30 measured samples |
-| Observed relative uncertainty | Main speed matrix: maximum 11.945%, with 6 of 102 rows above 10%; coverage-speed curve: maximum 16.775%, with 3 of 10 rows above 10%; no published row exceeded 20% |
+| Observed relative uncertainty | Main speed matrix: maximum 10.607%, with 2 of 105 rows above 10%; coverage-speed curve: maximum 12.142%, with 2 of 10 rows above 10%; no published row exceeded 20% |
 | Deterministic measurements | Corpus, patch-command distribution, exact-root counters, coverage accuracy, and pairwise stemming quality are evaluated without interpreting runtime scores; no warmup is required |
-| JVM reported by JMH | JDK 25.0.3, OpenJDK 64-Bit Server VM, 25.0.3+9 |
-| Java runtime | OpenJDK Runtime Environment, Red Hat build 25.0.3+9 |
+| JVM reported by JMH | JDK 25.0.4, OpenJDK 64-Bit Server VM, 25.0.4+7 |
+| Java runtime | OpenJDK Runtime Environment, Red Hat build 25.0.4+7 |
 | JVM invoker | `/usr/lib/jvm/java-25-openjdk/bin/java` |
 | Operating system | Fedora Linux 44 (MATE-Compiz) |
-| Kernel | Linux 7.1.4-200.fc44.x86_64 |
+| Kernel | Linux 7.1.7-200.fc44.x86_64 |
 | Architecture | x86_64 |
-| CPU | AMD Ryzen 5 8600G w/ Radeon 760M Graphics |
+| CPU | AMD Ryzen 5 7600 6-Core Processor |
 | Physical / logical CPUs | 6 / 12 |
 | CPU frequency policy | `amd-pstate-epp`; governor `performance` on every logical CPU; EPP `performance`; boost enabled |
 | CPU affinity | Scheduler default; no explicit pinning |
-| Installed memory | 60 GiB reported by the operating system |
-| Pre-run idle state | Load average 0.25 / 0.36 / 0.71 after the 120 s idle interval; CPU Tctl 40.2 degrees Celsius; swap unused |
-| End-of-run state | Load average 1.16 / 1.28 / 1.32; CPU Tctl 60.5 degrees Celsius |
+| Installed memory | 61 GiB reported by the operating system |
+| Pre-run idle state | Load average 0.16 / 0.42 / 0.88 after the 120 s idle interval; CPU Tctl 57.4 degrees Celsius; swap unused |
+| End-of-run state | Load average 1.59 / 1.49 / 1.36; CPU Tctl 78.1 degrees Celsius |
 | Power and idle policy | Developer workstation on stable power; screensaver, suspend, and hibernation disabled |
 | Concurrent project work | None during the published speed and coverage-speed run |

@@ -67,15 +67,15 @@ The JMH runtime classpath contains the optional model artifact because it is a s
 Generated local report files for this benchmark update:

 - `build/reports/jmh/benchmark-corpora.csv`
- `build/reports/jmh/stemmer-accuracy-2026-07-23.csv`
- `build/reports/jmh/stemmer-accuracy-2026-07-23.txt`
- `build/reports/jmh/stemmer-speed-2026-07-23.csv`
- `build/reports/jmh/stemmer-speed-2026-07-23.txt`
- `build/reports/jmh/english-coverage-accuracy-2026-07-23.csv`
- `build/reports/jmh/english-coverage-accuracy-2026-07-23.txt`
- `build/reports/jmh/english-coverage-speed-2026-07-23.csv`
- `build/reports/jmh/english-coverage-speed-2026-07-23.txt`
- `build/reports/jmh/performance-environment-2026-07-23.txt`
+- `build/reports/jmh/stemmer-accuracy-2026-08-10.csv`
+- `build/reports/jmh/stemmer-accuracy-2026-08-10.txt`
+- `build/reports/jmh/stemmer-speed-2026-08-10.csv`
+- `build/reports/jmh/stemmer-speed-2026-08-10.txt`
+- `build/reports/jmh/english-coverage-accuracy-2026-08-10.csv`
+- `build/reports/jmh/english-coverage-accuracy-2026-08-10.txt`
+- `build/reports/jmh/english-coverage-speed-2026-08-10.csv`
+- `build/reports/jmh/english-coverage-speed-2026-08-10.txt`
+- `build/reports/jmh/performance-environment-2026-08-10.txt`
 - `build/reports/stemming-quality/stemming-quality.csv`
 - `build/reports/stemming-quality/stemming-quality.md`
 - `build/reports/stemming-quality/metric-correlations-pearson.csv`
--- a/docs/benchmarks/reference/methodology.md
+++ b/docs/benchmarks/reference/methodology.md
@@ -2,7 +2,7 @@

 The stemmer comparison suite measures Radixor and Java stemmers on the same language and deterministic Radixor model dictionary-derived data. Published Radixor rows in this refresh use contracted compiled patch tries, where uniform preferred-command subtrees are collapsed into accepting leaves before the trie is frozen for lookup. For each language, the registered default model resource stores the expected root as the first tab-separated field on a line and its surface forms on the same line. Every single-token field on that line can therefore be paired with the same expected root.

-Published speed results come only from the exact method selection retained in `published-speed-benchmarks-2026-07-23.txt`. Internal `FrequencyTrie*` microbenchmarks, quality methods, the CISTEM gold-standard experiment, and the optional `PolishPolimorfStemmerComparisonBenchmark` are not part of those results.
+Published speed results come only from the exact method selection retained in `published-speed-benchmarks-2026-08-10.txt`. Internal `FrequencyTrie*` microbenchmarks, quality methods, the CISTEM gold-standard experiment, and the optional `PolishPolimorfStemmerComparisonBenchmark` are not part of those results. The Snowball 3.1.0 refresh adds direct Czech, Persian, and Polish workloads; the existing Radixor and Lucene workload domains are unchanged.

 ## Benchmark Passes

@@ -41,8 +41,8 @@ For right-to-left Radixor languages, patch application uses the traversal direct

 The quality pass reports exact-root agreement against the expected root from the default-model dictionary line. External-stemmer counters are written to:

- `build/reports/jmh/stemmer-accuracy-2026-07-23.csv`
- `build/reports/jmh/stemmer-accuracy-2026-07-23.txt`
+- `build/reports/jmh/stemmer-accuracy-2026-08-10.csv`
+- `build/reports/jmh/stemmer-accuracy-2026-08-10.txt`

 Accuracy is computed from standard JMH secondary rows:

--- a/docs/benchmarks/reference/reproducibility.md
+++ b/docs/benchmarks/reference/reproducibility.md
@@ -4,19 +4,28 @@

 - Machine-readable CSV: [stemming-quality.csv](../data/stemming-quality.csv)
 - SHA-256 record: [stemming-quality.sha256](../data/stemming-quality.sha256)
- SHA-256: `edf16b07be8a535943ddf37caeb8807755c95e9e1fb13244145f28be74b491d8`
- Complete scenarios: 308
+- SHA-256: `d34f325da320a2e040b54d8d8b5c216d70448f08cfb8659a423e99882aa1afb5`
+- Complete scenarios: 314
 - Authoritative language universe: 20 languages
- Language-page scenarios: 308 across 20 benchmark pages
+- Language-page scenarios: 314 across 20 benchmark pages

 The CSV contains the model ID, independent model version, descriptor SHA-256, raw pair counts, raw over/under numerators and denominators, candidate statistics, and relation metrics. Reserved partition-metric columns remain empty because the gold standard is an overlapping cover. Documentation is regenerated from this file rather than manually transcribed. Publication fails when any row uses a model other than the language's registered default.

 ## Commands

 ```bash
-./gradlew stemmingQuality
-./gradlew publishStemmingQualityDocumentation
-./gradlew verifyStemmingQualityDocumentation
+./gradlew --no-daemon stemmingQuality \
+    publishStemmingQualityDocumentation \
+    verifyStemmingQualityDocumentation
+./gradlew --no-daemon benchmarkCorpusReport writeJmhRuntimeClasspath
+tools/run-published-accuracy-benchmarks.sh 2026-08-10
+tools/run-published-speed-benchmarks.sh 2026-08-10
+python3 tools/update-benchmark-documentation.py \
+    --corpus build/reports/jmh/benchmark-corpora.csv \
+    --accuracy build/reports/jmh/stemmer-accuracy-2026-08-10.csv \
+    --speed build/reports/jmh/stemmer-speed-2026-08-10.csv \
+    --coverage-accuracy build/reports/jmh/english-coverage-accuracy-2026-08-10.csv \
+    --coverage-speed build/reports/jmh/english-coverage-speed-2026-08-10.csv
 ./gradlew test
 ./gradlew prepareMkDocsSource
 mkdocs build --strict --config-file build/mkdocs/mkdocs.yml
@@ -59,18 +68,19 @@ The Pages workflow publishes that staged documentation together with Javadoc, JU

 ## Performance benchmark reproduction

-The current speed and coverage-speed command is:
+The current accuracy, speed, and coverage commands are:

 ```bash
-./gradlew writeJmhRuntimeClasspath --no-daemon
-tools/run-published-speed-benchmarks.sh 2026-07-23
+./gradlew --no-daemon benchmarkCorpusReport writeJmhRuntimeClasspath
+tools/run-published-accuracy-benchmarks.sh 2026-08-10
+tools/run-published-speed-benchmarks.sh 2026-08-10
 ```

-The runner refuses to start unless every CPU uses the `performance` governor, materializes the exact selected benchmark list, rejects quality/Polimorf/gold-standard methods, and requires the Hebrew speed path. It records hardware, JVM, source-state, JAR, classpath, corpus, quality, load, temperature, and governor provenance before running. The exact JMH configuration is listed in [Environment and reports](environment.md). Quality and performance reports are separate datasets and are not combined into an undocumented scalar.
+The speed runner refuses to start unless every CPU uses the `performance` governor, materializes the exact selected benchmark list, rejects quality/Polimorf/gold-standard methods, and requires the Hebrew speed path. It records hardware, JVM, source-state, JAR, classpath, corpus, quality, load, temperature, and governor provenance before running. The accuracy runner evaluates all four exact-root benchmark classes and verifies that every new Snowball 3.1.0 candidate exposes all six accuracy counters. The exact JMH configuration is listed in [Environment and reports](environment.md). Quality and performance reports are separate datasets and are not combined into an undocumented scalar.

 ## Recorded and unavailable provenance

-The performance documentation records its 2026-07-23 environment, JDK 25.0.3, operating system, hardware, base revision, exact dirty patch, untracked-source checksums, executable JMH JAR checksum, and model descriptor checksums. The quality CSV embeds model identity and checksum in every row; run date, core source state, JVM, OS, and hardware are shared provenance on the environment page.
+The performance documentation records its 2026-08-10 environment, JDK, operating system, hardware, base revision, exact dirty patch, untracked-source checksums, executable JMH JAR checksum, and model descriptor checksums. The quality CSV embeds model identity and checksum in every row; run date, core source state, JVM, OS, and hardware are shared provenance on the environment page.

 Exact immutable upstream revisions were not recorded for every legacy UniMorph import. That limitation remains explicit in model descriptors and cannot be repaired from filesystem timestamps. Dependency versions reproducible from repository configuration include Apache Lucene 10.5.0, Morfologik 2.1.9, the Ukrainian dictionary artifact 4.9.1, and JMH 1.37.

--- a/docs/benchmarks/reference/tested-stemmers.md
+++ b/docs/benchmarks/reference/tested-stemmers.md
@@ -4,10 +4,10 @@ The JMH adapter registry is authoritative for evaluated implementations and lang

 | Family or implementation | Upstream / attribution | Tested version or revision | Evaluated scope | Output capability and adapter behaviour | Interpretation notes |
 | --- | --- | --- | --- | --- | --- |
-| Radixor | Egothor / Radixor project | Base commit and measured working-tree state recorded on the environment page | All 20 reconciled default model languages; all 20 have benchmark pages | Deterministic preferred patch via `get`; ranked distinct alternatives via `getAll`; primary is always included | Model-dictionary-derived compiled patch trie. Default rows use each language's stable default model ID. |
+| Radixor | Egothor / Radixor project | Base commit and measured working-tree state recorded on the environment page | All 20 reconciled default model languages; all 20 have benchmark pages | Deterministic preferred patch via `get`; ranked distinct alternatives via `getAll`; primary is always included | Dictionary-trained compiled patch trie. Default rows use each language's stable default model ID. |
 | Apache Lucene language stem filters | Apache Lucene project | 10.5.0 | Adapter-declared language-specific subsets | TokenFilter lifecycle and language normalization match JMH; normally single-output | Light, minimal, possessive, and language stem filters deliberately implement different scopes. Narrow scope is not a defect. |
 | Apache Lucene SnowballFilter | Apache Lucene project using Snowball algorithms | Lucene 10.5.0 | Snowball-supported subset of Radixor languages | Single primary token emitted through the Lucene TokenFilter path | Includes TokenStream overhead and required normalization. |
-| Official Snowball Java | Snowball project | Repository preparation downloads the configured upstream Java distribution; an immutable revision was not recorded in the quality CSV | Same-language adapter subset | Direct generated Java API; single output | Rule-based suffix algorithms provide broad baselines rather than dictionary-root guarantees. |
+| Official Snowball Java | Snowball project | 3.1.0 source distribution; SHA-256 `5dab34d491f55f47b6e971569ffe6aadf5991512c648ddfe5d331b494cf6d655` | 17 same-language direct adapters, including the Czech, Persian, and Polish stemmers added in 3.1.0 | Direct generated Java API; single output | Rule-based suffix algorithms provide broad baselines rather than dictionary-root guarantees. Lucene 10.5.0 does not yet expose the three new algorithms through `SnowballFilter`, so those rows are direct-only. |
 | Lucene Stempel | Apache Lucene / Polish stemming tables | Lucene 10.5.0 | Polish | Direct and TokenFilter paths where registered; single primary output | Table-driven Polish implementation. |
 | Morfologik | Morfologik project; Lucene integration by Apache Lucene | Morfologik 2.1.9, Lucene integration 10.5.0; Ukrainian dictionary artifact 4.9.1 | Registered Polish and Ukrainian paths | Deterministic first lemma for primary comparison; all distinct lemma strings for candidate policies | Several analyses may share a lemma and are deduplicated by exact string equality. |
 | Hunspell via Lucene | Hunspell dictionaries from the `wooorm/dictionaries` repository; adapter by Apache Lucene | Lucene 10.5.0; dictionary repository revision was not recorded | Configured German, English, Spanish, French, Dutch, Polish, and Ukrainian dictionaries | First emitted stem is primary; all distinct stems at the token position are candidates | Dictionary content and affix rules differ by language. |