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Radixor/docs/benchmarks/languages/czech.md
Leo Galambos 05f3855b99 feat(benchmarks): expand multilingual stemming quality evaluation 
* cover all Radixor dictionary languages
* add PRIMARY_OUTPUT, ANY_CANDIDATE, and ALL_CANDIDATES policies
* measure pairwise over-stemming and under-stemming
* add balanced accuracy and complementary quality metrics
* compare single-output and multi-output stemmers fairly
* improve result validation, reporting, and documentation
* move stemming quality tests into the standard test source set
* preserve the existing JMH benchmark structure and badge output
2026-07-20 23:20:17 +02:00

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Czech Stemmer Benchmarks

This page reports same-language stemming benchmarks for Czech. Accuracy is listed first because speed without root agreement is not enough to interpret stemmer quality.

All speed values are environment-specific and were measured on the hardware and JVM listed in the benchmark overview. Speed benchmark operations process changed dictionary tokens only. Accuracy uses the complete Radixor dictionary for the language.

Radixor must not be read as simply "slower" when a narrow competitor has a lower timing row. In these tables Radixor is the quality-oriented baseline: its exact-root accuracy is typically close to 100%, while many faster rule-based, light, minimal, or possessive filters reach that speed by doing much less linguistic work and often score far lower in All exact and Changed exact. The Radixor rows in this benchmark refresh use the contracted compiled patch trie: compilation collapses uniform patch-command subtrees into accepting leaves, reducing hot lookup depth while preserving the preferred stemming result measured by the accuracy pass. The EnglishRadixorDictionaryCoverageBenchmark table shows the resulting quality/speed envelope explicitly. The same interpretation applies to this language page: speed rows must be read together with the accuracy table above them.

Dictionary Corpus

Resource Dictionary rows Complete quality tokens Already-root tokens Changed speed tokens
CS_CZ 5,113 56,612 10,049 46,563

Radixor Patch Command Distribution

Radixor stores the preferred transformation for each normalized dictionary word form as a compiled patch command. This distribution shows which runtime command class is selected by the trained trie for the complete language dictionary. The total number of preferred patch commands analyzed for this language is 56,612.

Command class Meaning Word forms Share
AppendCharacterCommand Appends one character to the end of the word form. 675 1.192%
BackwardCompoundCommand Applies a multi-step backward patch made from skip, delete, insert, and replace operations. 22,681 40.064%
DeleteSuffixCommand Deletes one or more trailing characters from the word form. 14,980 26.461%
PreserveCommand Returns the word form unchanged because it already matches the preferred root. 10,109 17.857%
ReplaceLastCharacterCommand Replaces the final character of the word form. 8,167 14.426%

Accuracy

Accuracy is computed from JMH auxiliary counters in the current report. The counters are deterministic for a fixed corpus and stemmer; percentages divide matching counters by evaluated counters from the same report and are not timing metrics.

Stemmer All exact Changed exact Root preserved Note
Radixor 99.465% 99.439% 99.582% Full Radixor dictionary 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.

Speed

Speed uses JMH average time, 3 warmup iterations, 5 measurement iterations, 1 fork, 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 czechRadixor 3.332 0.240 71.6 1.000 Full Radixor dictionary patch-command stemmer.
Lucene HunspellStemFilter luceneHunspellStemFilter 346.819 3.622 7448.4 104.091 Benchmark-only Czech Hunspell dictionary compared via Lucene HunspellStemFilter.
Lucene CzechStemFilter czechLuceneCzechStemFilter 3.163 0.253 67.9 0.949 Czech suffix stemmer implemented as a 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.
  • 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.
  • Snowball rows are rule-based generated suffix stemmers; they are useful algorithmic baselines, not dictionary-root equivalence guarantees.

Stemming Quality

Runtime performance and linguistic grouping quality are independent dimensions. This section evaluates language CS_CZ using the complete validated stemming-quality result matrix. Every usable dictionary row is one gold-standard group of forms expected to share a morphological family or lemma. Exact equality with a predetermined lemma is not required. Same-row pairs are positive pairs; pairs from different rows are negative pairs.

ALL_WORDS includes every valid group and its original forms. LOWERCASE_GROUPS_ONLY excludes an entire group when any Unicode code point is uppercase or titlecase; retained words are not lowercased or otherwise rewritten. This isolates case-handling effects without changing retained inputs. Download the complete machine-readable result snapshot.

Evaluation Scope and Key Findings

The dictionary resource is src/main/resources/cs_cz/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 0.996565 among 3 deterministic stemmers. The runner-up is HUNSPELL CZECH LUCENE FILTER at 0.853752, a difference of 0.142813. This rank does not imply leadership in throughput or every secondary metric.
  • LOWERCASE_GROUPS_ONLY: Radixor ranks first by balanced accuracy at 0.997139 among 3 deterministic stemmers. The runner-up is HUNSPELL CZECH LUCENE FILTER at 0.852770, a difference of 0.144369. 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. Rankings are separated by output policy and ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. Balanced accuracy is a navigation metric, not a universally authoritative quality score.

PRIMARY_OUTPUT ranking

Rank Stemmer Output policy Balanced accuracy Over-stemming Under-stemming F0.5 F1 MCC
1 Radixor PRIMARY_OUTPUT 0.996565 3867 / 1334876815 (0.000290%) 2073 / 301835 (0.686799%) 0.988432 0.990189 0.990191
2 HUNSPELL CZECH LUCENE FILTER PRIMARY_OUTPUT 0.853752 11408 / 1334876815 (0.000855%) 88283 / 301835 (29.248762%) 0.888560 0.810759 0.819499
3 CZECH LUCENE CZECH STEM FILTER PRIMARY_OUTPUT 0.793614 14480 / 1334876815 (0.001085%) 124586 / 301835 (41.276194%) 0.829234 0.718241 0.736765
Classification metrics
Rank Stemmer Output policy Precision Recall Specificity Balanced accuracy Pairwise accuracy Error rate
1 Radixor PRIMARY_OUTPUT 0.987264 0.993132 0.999997 0.996565 0.999996 0.000004
2 HUNSPELL CZECH LUCENE FILTER PRIMARY_OUTPUT 0.949289 0.707512 0.999991 0.853752 0.999925 0.000075
3 CZECH LUCENE CZECH STEM FILTER PRIMARY_OUTPUT 0.924477 0.587238 0.999989 0.793614 0.999896 0.000104
Pair-relation metrics
Rank Stemmer Output policy F0.5 F1 F2 Jaccard Fowlkes–Mallows MCC
1 Radixor PRIMARY_OUTPUT 0.988432 0.990189 0.991953 0.980569 0.990194 0.990191
2 HUNSPELL CZECH LUCENE FILTER PRIMARY_OUTPUT 0.888560 0.810759 0.745486 0.681745 0.819533 0.819499
3 CZECH LUCENE CZECH STEM FILTER PRIMARY_OUTPUT 0.829234 0.718241 0.633453 0.560356 0.736809 0.736765
Partition metrics (PRIMARY_OUTPUT only)
Rank Stemmer Output policy Adjusted Rand Index Homogeneity Completeness V-measure Normalized mutual information
1 Radixor PRIMARY_OUTPUT 0.990187 0.998733 0.998686 0.998709 0.998709
2 HUNSPELL CZECH LUCENE FILTER PRIMARY_OUTPUT 0.810723 0.995777 0.952852 0.973842 0.973842
3 CZECH LUCENE CZECH STEM FILTER PRIMARY_OUTPUT 0.718192 0.993801 0.944977 0.968774 0.968774
Raw pair counts
Rank Stemmer Output policy TP FP FN TN Over error / possible Under error / possible
1 Radixor PRIMARY_OUTPUT 299762 3867 2073 1334872948 3867 / 1334876815 2073 / 301835
2 HUNSPELL CZECH LUCENE FILTER PRIMARY_OUTPUT 213552 11408 88283 1334865407 11408 / 1334876815 88283 / 301835
3 CZECH LUCENE CZECH STEM FILTER PRIMARY_OUTPUT 177249 14480 124586 1334862335 14480 / 1334876815 124586 / 301835

ANY_CANDIDATE ranking

Rank Stemmer Output policy Balanced accuracy Over-stemming Under-stemming F0.5 F1 MCC
1 Radixor ANY_CANDIDATE 1.000000 0 / 1334876815 (0.000000%) 0 / 301835 (0.000000%) 1.000000 1.000000 1.000000
2 HUNSPELL CZECH LUCENE FILTER ANY_CANDIDATE 0.871577 10102 / 1334876815 (0.000757%) 77523 / 301835 (25.683900%) 0.904855 0.836596 0.843258
Classification metrics
Rank Stemmer Output policy Precision Recall Specificity Balanced accuracy Pairwise accuracy Error rate
1 Radixor ANY_CANDIDATE 1.000000 1.000000 1.000000 1.000000 1.000000 0.000000
2 HUNSPELL CZECH LUCENE FILTER ANY_CANDIDATE 0.956905 0.743161 0.999992 0.871577 0.999934 0.000066
Pair-relation metrics
Rank Stemmer Output policy F0.5 F1 F2 Jaccard Fowlkes–Mallows MCC
1 Radixor ANY_CANDIDATE 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000
2 HUNSPELL CZECH LUCENE FILTER ANY_CANDIDATE 0.904855 0.836596 0.777914 0.719094 0.843288 0.843258
Partition metrics (PRIMARY_OUTPUT only)
Rank Stemmer Output policy Adjusted Rand Index Homogeneity Completeness V-measure Normalized mutual information
1 Radixor ANY_CANDIDATE n/a n/a n/a n/a n/a
2 HUNSPELL CZECH LUCENE FILTER ANY_CANDIDATE n/a n/a n/a n/a n/a
Raw pair counts
Rank Stemmer Output policy TP FP FN TN Over error / possible Under error / possible
1 Radixor ANY_CANDIDATE 301835 0 0 1334876815 0 / 1334876815 0 / 301835
2 HUNSPELL CZECH LUCENE FILTER ANY_CANDIDATE 224312 10102 77523 1334866713 10102 / 1334876815 77523 / 301835

ALL_CANDIDATES ranking

Rank Stemmer Output policy Balanced accuracy Over-stemming Under-stemming F0.5 F1 MCC
1 Radixor ALL_CANDIDATES 0.999998 5850 / 1334876815 (0.000438%) 0 / 301835 (0.000000%) 0.984732 0.990402 0.990446
2 HUNSPELL CZECH LUCENE FILTER ALL_CANDIDATES 0.871575 13917 / 1334876815 (0.001043%) 77523 / 301835 (25.683900%) 0.893851 0.830687 0.836477
Classification metrics
Rank Stemmer Output policy Precision Recall Specificity Balanced accuracy Pairwise accuracy Error rate
1 Radixor ALL_CANDIDATES 0.980987 1.000000 0.999996 0.999998 0.999996 0.000004
2 HUNSPELL CZECH LUCENE FILTER ALL_CANDIDATES 0.941581 0.743161 0.999990 0.871575 0.999932 0.000068
Pair-relation metrics
Rank Stemmer Output policy F0.5 F1 F2 Jaccard Fowlkes–Mallows MCC
1 Radixor ALL_CANDIDATES 0.984732 0.990402 0.996139 0.980987 0.990448 0.990446
2 HUNSPELL CZECH LUCENE FILTER ALL_CANDIDATES 0.893851 0.830687 0.775861 0.710406 0.836509 0.836477
Partition metrics (PRIMARY_OUTPUT only)
Rank Stemmer Output policy Adjusted Rand Index Homogeneity Completeness V-measure Normalized mutual information
1 Radixor ALL_CANDIDATES n/a n/a n/a n/a n/a
2 HUNSPELL CZECH LUCENE FILTER ALL_CANDIDATES n/a n/a n/a n/a n/a
Raw pair counts
Rank Stemmer Output policy TP FP FN TN Over error / possible Under error / possible
1 Radixor ALL_CANDIDATES 301835 5850 0 1334870965 5850 / 1334876815 0 / 301835
2 HUNSPELL CZECH LUCENE FILTER ALL_CANDIDATES 224312 13917 77523 1334862898 13917 / 1334876815 77523 / 301835

Multi-output analysis

Alternative candidates are capability analyses, not replacements for the deterministic comparison.

Stemmer Under pairs repaired Best-case over pairs avoided All-candidate collisions added Multi-candidate forms Multi-candidate share Maximum candidates Total candidate assignments
Radixor 2073 3867 1983 596 1.153340% 4 52319
HUNSPELL CZECH LUCENE FILTER 10760 1306 2509 3317 6.418840% 5 55596

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. Rankings are separated by output policy and ordered by unrounded balanced accuracy, followed by MCC, F1, over-stemming rate, over-stemming count, under-stemming rate, and stemmer. Balanced accuracy is a navigation metric, not a universally authoritative quality score.

PRIMARY_OUTPUT ranking

Rank Stemmer Output policy Balanced accuracy Over-stemming Under-stemming F0.5 F1 MCC
1 Radixor PRIMARY_OUTPUT 0.997139 3863 / 1298544215 (0.000297%) 1709 / 298813 (0.571930%) 0.988580 0.990710 0.990714
2 HUNSPELL CZECH LUCENE FILTER PRIMARY_OUTPUT 0.852770 11239 / 1298544215 (0.000866%) 87986 / 298813 (29.445171%) 0.888009 0.809505 0.818403
3 CZECH LUCENE CZECH STEM FILTER PRIMARY_OUTPUT 0.791794 13950 / 1298544215 (0.001074%) 124426 / 298813 (41.640089%) 0.828709 0.715948 0.735055
Classification metrics
Rank Stemmer Output policy Precision Recall Specificity Balanced accuracy Pairwise accuracy Error rate
1 Radixor PRIMARY_OUTPUT 0.987165 0.994281 0.999997 0.997139 0.999996 0.000004
2 HUNSPELL CZECH LUCENE FILTER PRIMARY_OUTPUT 0.949389 0.705548 0.999991 0.852770 0.999924 0.000076
3 CZECH LUCENE CZECH STEM FILTER PRIMARY_OUTPUT 0.925931 0.583599 0.999989 0.791794 0.999893 0.000107
Pair-relation metrics
Rank Stemmer Output policy F0.5 F1 F2 Jaccard Fowlkes–Mallows MCC
1 Radixor PRIMARY_OUTPUT 0.988580 0.990710 0.992849 0.981591 0.990716 0.990714
2 HUNSPELL CZECH LUCENE FILTER PRIMARY_OUTPUT 0.888009 0.809505 0.743753 0.679973 0.818437 0.818403
3 CZECH LUCENE CZECH STEM FILTER PRIMARY_OUTPUT 0.828709 0.715948 0.630198 0.557569 0.735100 0.735055
Partition metrics (PRIMARY_OUTPUT only)
Rank Stemmer Output policy Adjusted Rand Index Homogeneity Completeness V-measure Normalized mutual information
1 Radixor PRIMARY_OUTPUT 0.990708 0.998726 0.999030 0.998878 0.998878
2 HUNSPELL CZECH LUCENE FILTER PRIMARY_OUTPUT 0.809467 0.995812 0.952394 0.973619 0.973619
3 CZECH LUCENE CZECH STEM FILTER PRIMARY_OUTPUT 0.715897 0.993897 0.944297 0.968463 0.968463
Raw pair counts
Rank Stemmer Output policy TP FP FN TN Over error / possible Under error / possible
1 Radixor PRIMARY_OUTPUT 297104 3863 1709 1298540352 3863 / 1298544215 1709 / 298813
2 HUNSPELL CZECH LUCENE FILTER PRIMARY_OUTPUT 210827 11239 87986 1298532976 11239 / 1298544215 87986 / 298813
3 CZECH LUCENE CZECH STEM FILTER PRIMARY_OUTPUT 174387 13950 124426 1298530265 13950 / 1298544215 124426 / 298813

ANY_CANDIDATE ranking

Rank Stemmer Output policy Balanced accuracy Over-stemming Under-stemming F0.5 F1 MCC
1 Radixor ANY_CANDIDATE 1.000000 0 / 1298544215 (0.000000%) 0 / 298813 (0.000000%) 1.000000 1.000000 1.000000
2 HUNSPELL CZECH LUCENE FILTER ANY_CANDIDATE 0.870432 10028 / 1298544215 (0.000772%) 77431 / 298813 (25.912862%) 0.904004 0.835052 0.841852
Classification metrics
Rank Stemmer Output policy Precision Recall Specificity Balanced accuracy Pairwise accuracy Error rate
1 Radixor ANY_CANDIDATE 1.000000 1.000000 1.000000 1.000000 1.000000 0.000000
2 HUNSPELL CZECH LUCENE FILTER ANY_CANDIDATE 0.956666 0.740871 0.999992 0.870432 0.999933 0.000067
Pair-relation metrics
Rank Stemmer Output policy F0.5 F1 F2 Jaccard Fowlkes–Mallows MCC
1 Radixor ANY_CANDIDATE 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000
2 HUNSPELL CZECH LUCENE FILTER ANY_CANDIDATE 0.904004 0.835052 0.775874 0.716815 0.841883 0.841852
Partition metrics (PRIMARY_OUTPUT only)
Rank Stemmer Output policy Adjusted Rand Index Homogeneity Completeness V-measure Normalized mutual information
1 Radixor ANY_CANDIDATE n/a n/a n/a n/a n/a
2 HUNSPELL CZECH LUCENE FILTER ANY_CANDIDATE n/a n/a n/a n/a n/a
Raw pair counts
Rank Stemmer Output policy TP FP FN TN Over error / possible Under error / possible
1 Radixor ANY_CANDIDATE 298813 0 0 1298544215 0 / 1298544215 0 / 298813
2 HUNSPELL CZECH LUCENE FILTER ANY_CANDIDATE 221382 10028 77431 1298534187 10028 / 1298544215 77431 / 298813

ALL_CANDIDATES ranking

Rank Stemmer Output policy Balanced accuracy Over-stemming Under-stemming F0.5 F1 MCC
1 Radixor ALL_CANDIDATES 0.999998 5782 / 1298544215 (0.000445%) 0 / 298813 (0.000000%) 0.984756 0.990418 0.990461
2 HUNSPELL CZECH LUCENE FILTER ALL_CANDIDATES 0.870430 13601 / 1298544215 (0.001047%) 77431 / 298813 (25.912862%) 0.893574 0.829463 0.835425
Classification metrics
Rank Stemmer Output policy Precision Recall Specificity Balanced accuracy Pairwise accuracy Error rate
1 Radixor ALL_CANDIDATES 0.981017 1.000000 0.999996 0.999998 0.999996 0.000004
2 HUNSPELL CZECH LUCENE FILTER ALL_CANDIDATES 0.942119 0.740871 0.999990 0.870430 0.999930 0.000070
Pair-relation metrics
Rank Stemmer Output policy F0.5 F1 F2 Jaccard Fowlkes–Mallows MCC
1 Radixor ALL_CANDIDATES 0.984756 0.990418 0.996145 0.981017 0.990463 0.990461
2 HUNSPELL CZECH LUCENE FILTER ALL_CANDIDATES 0.893574 0.829463 0.773936 0.708617 0.835457 0.835425
Partition metrics (PRIMARY_OUTPUT only)
Rank Stemmer Output policy Adjusted Rand Index Homogeneity Completeness V-measure Normalized mutual information
1 Radixor ALL_CANDIDATES n/a n/a n/a n/a n/a
2 HUNSPELL CZECH LUCENE FILTER ALL_CANDIDATES n/a n/a n/a n/a n/a
Raw pair counts
Rank Stemmer Output policy TP FP FN TN Over error / possible Under error / possible
1 Radixor ALL_CANDIDATES 298813 5782 0 1298538433 5782 / 1298544215 0 / 298813
2 HUNSPELL CZECH LUCENE FILTER ALL_CANDIDATES 221382 13601 77431 1298530614 13601 / 1298544215 77431 / 298813

Multi-output analysis

Alternative candidates are capability analyses, not replacements for the deterministic comparison.

Stemmer Under pairs repaired Best-case over pairs avoided All-candidate collisions added Multi-candidate forms Multi-candidate share Maximum candidates Total candidate assignments
Radixor 1709 3863 1919 540 1.059488% 4 51543
HUNSPELL CZECH LUCENE FILTER 10555 1211 2362 3237 6.351044% 5 54804

Output Policies and Metric Definitions

PRIMARY_OUTPUT uses one deterministic stem per form and therefore defines a strict partition. ANY_CANDIDATE is an optimistic oracle-assisted pairwise upper bound: a same-group pair succeeds when candidates intersect, while a different-group pair succeeds when a non-colliding selection exists. Candidate choices may differ between pairs, so this is not deterministic runtime behaviour and need not represent one globally consistent assignment. ALL_CANDIDATES activates every returned candidate; forms are related when candidate sets intersect. Alternatives can reduce under-stemming but can introduce cross-group collisions, and the resulting relation can overlap and need not be a partition.

For each row, TP = underPossiblePairs - underErrorPairs, FN = underErrorPairs, FP = overErrorPairs, and TN = overPossiblePairs - overErrorPairs. TP and FN concern same-group pairs; FP and TN concern different-group pairs. Consequently, under-stemming and over-stemming use different denominators. Undefined values are rendered as n/a.

  • Under-stemming rate: FN / (TP + FN), the false-negative rate over same-group pairs.
  • Over-stemming rate: FP / (TN + FP), the false-positive rate over different-group pairs.
  • Pairwise precision: TP / (TP + FP), the fraction of predicted conflations that are gold-standard positive pairs.
  • Pairwise recall: TP / (TP + FN), the fraction of gold-standard positive pairs successfully connected.
  • Pairwise specificity: TN / (TN + FP), the fraction of different-group pairs correctly separated.
  • Balanced accuracy: (recall + specificity) / 2. It gives equal weight to positive and negative pair classes and is less dominated by the large true-negative class than ordinary accuracy. It does not replace the raw errors or other metrics.
  • Pairwise F-beta: ((1 + betaSquared) * TP) / (((1 + betaSquared) * TP) + (betaSquared * FN) + FP). F0.5 emphasizes precision and penalizes over-stemming more; F1 weights precision and recall equally; F2 emphasizes recall and penalizes under-stemming more.
  • MCC: (TP * TN - FP * FN) / sqrt((TP + FP) * (TP + FN) * (TN + FP) * (TN + FN)). It uses all confusion counts and remains useful under class imbalance, except when its denominator is degenerate.
  • Jaccard index: TP / (TP + FP + FN).
  • Fowlkes–Mallows index: sqrt(precision * recall).
  • Pairwise accuracy: (TP + TN) / (TP + TN + FP + FN). It can be dominated by true-negative cross-group pairs.
  • Pairwise error rate: (FP + FN) / (TP + TN + FP + FN).

Adjusted Rand Index uses the gold/predicted contingency table and chance correction. Homogeneity is 1 - H(gold | predicted) / H(gold); completeness is 1 - H(predicted | gold) / H(predicted); V-measure is their harmonic mean; normalized mutual information uses the arithmetic-mean entropy normalization MI / ((H(gold) + H(predicted)) / 2). These partition-only metrics apply to PRIMARY_OUTPUT; candidate-relation rows show n/a.

Provenance

  • Authoritative source: docs/benchmarks/data/stemming-quality.csv
  • Source SHA-256: 5a93a6ab60e46489737cd649eb1ac48182114b9038f7f20195ab9d1c1fc0dd28
  • Evaluation command: ./gradlew stemmingQuality
  • Dictionary language: CS_CZ
  • Processing modes: ALL_WORDS, LOWERCASE_GROUPS_ONLY
  • Stemmer versions and transitive artifacts: resolved by the repository's JMH Gradle configuration and gradle.lockfile
  • Radixor version, Git revision, generation date, JDK version, operating system, and dictionary revision: not recorded in the authoritative CSV
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