Files
Radixor/docs/benchmarks/languages/spanish.md
Leo Galambos 38620d7e71 feat: prepare Radixor 3.0.0 with contracted tries and compiled patch commands
Introduce contracted compiled patch tries for faster lookup, make compiled
patch commands the primary runtime path, refresh stemmer benchmarks and
documentation, and restructure the documentation for 3.0.0 onboarding.

BREAKING CHANGE: Radixor 3.0.0 promotes compiled patch-command APIs and
new compiled trie artifacts as the primary runtime integration model.
2026-07-03 18:44:39 +02:00

5.6 KiB

Spanish Stemmer Benchmarks

This page reports same-language stemming benchmarks for Spanish. 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
ES_ES 65,059 926,393 120,121 806,272

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 926,393.

Command class Meaning Word forms Share
AppendCharacterCommand Appends one character to the end of the word form. 5,367 0.579%
BackwardCompoundCommand Applies a multi-step backward patch made from skip, delete, insert, and replace operations. 524,682 56.637%
DeleteSuffixCommand Deletes one or more trailing characters from the word form. 240,872 26.001%
PreserveCommand Returns the word form unchanged because it already matches the preferred root. 130,089 14.043%
ReplaceLastCharacterCommand Replaces the final character of the word form. 25,383 2.740%

Accuracy

Accuracy is computed from one deterministic JMH measurement iteration without warmup. The benchmark may execute the full dictionary pass more than once inside that single timed iteration; percentages divide matching counters by evaluated counters from the same iteration.

Stemmer All exact Changed exact Root preserved Note
Radixor 97.459% 97.544% 96.891% Full Radixor dictionary patch-command stemmer.
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 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, 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 spanishRadixor 64.539 3.448 80.0 1.000 Full Radixor dictionary patch-command stemmer.
Lucene SpanishMinimalStemFilter spanishLuceneSpanishMinimalStemFilter 38.288 2.382 47.5 0.593 Minimal Spanish suffix reducer; narrow baseline.
Lucene SpanishLightStemFilter spanishLuceneSpanishLightStemFilter 40.855 2.407 50.7 0.633 Light Spanish suffix stemmer.
Lucene SpanishPluralStemFilter spanishLuceneSpanishPluralStemFilter 91.054 8.822 112.9 1.411 Plural-oriented Spanish suffix reducer.
Official Snowball direct snowballDirect[SPANISH] 168.813 32.860 209.4 2.616 Official Snowball generated Java stemmer; direct API.
Lucene SnowballFilter luceneSnowballFilter[SPANISH] 185.626 50.297 230.2 2.876 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.
  • 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.