@Test public void testLemmasAsArray() throws Exception { String[] lemmas = lemmatizer.lemmatize(tokens, postags); Assert.assertArrayEquals(expect, lemmas); }
public String[] lemmatize(String[] toks, String[] tags) { String[] ses = predictSES(toks, tags); String[] lemmas = decodeLemmas(toks, ses); return lemmas; }
LemmatizerME implements Lemmatizer { public String[] lemmatize(String[] toks, String[] tags) { String[] ses = predictSES(toks, tags); String[] lemmas = decodeLemmas(toks, ses); return lemmas; } }
LemmatizerME implements Lemmatizer { public String[] lemmatize(String[] toks, String[] tags) { String[] ses = predictSES(toks, tags); String[] lemmas = decodeLemmas(toks, ses); return lemmas; } LemmatizerME(LemmatizerModel model); }
LemmatizerME implements Lemmatizer { public String[] lemmatize(String[] toks, String[] tags) { String[] ses = predictSES(toks, tags); String[] lemmas = decodeLemmas(toks, ses); return lemmas; } LemmatizerME(LemmatizerModel model); String[] lemmatize(String[] toks, String[] tags); @Override List<List<String>> lemmatize(List<String> toks,
      List<String> tags); String[] predictSES(String[] toks, String[] tags); String[][] predictLemmas(int numLemmas, String[] toks, String[] tags); static String[] decodeLemmas(String[] toks, String[] preds); static String[] encodeLemmas(String[] toks, String[] lemmas); Sequence[] topKSequences(String[] sentence, String[] tags); Sequence[] topKSequences(String[] sentence, String[] tags, double minSequenceScore); void probs(double[] probs); double[] probs(); static LemmatizerModel train(String languageCode,
      ObjectStream<LemmaSample> samples, TrainingParameters trainParams,
      LemmatizerFactory posFactory); Sequence[] topKLemmaClasses(String[] sentence, String[] tags); Sequence[] topKLemmaClasses(String[] sentence, String[] tags, double minSequenceScore); }
LemmatizerME implements Lemmatizer { public String[] lemmatize(String[] toks, String[] tags) { String[] ses = predictSES(toks, tags); String[] lemmas = decodeLemmas(toks, ses); return lemmas; } LemmatizerME(LemmatizerModel model); String[] lemmatize(String[] toks, String[] tags); @Override List<List<String>> lemmatize(List<String> toks,
      List<String> tags); String[] predictSES(String[] toks, String[] tags); String[][] predictLemmas(int numLemmas, String[] toks, String[] tags); static String[] decodeLemmas(String[] toks, String[] preds); static String[] encodeLemmas(String[] toks, String[] lemmas); Sequence[] topKSequences(String[] sentence, String[] tags); Sequence[] topKSequences(String[] sentence, String[] tags, double minSequenceScore); void probs(double[] probs); double[] probs(); static LemmatizerModel train(String languageCode,
      ObjectStream<LemmaSample> samples, TrainingParameters trainParams,
      LemmatizerFactory posFactory); Sequence[] topKLemmaClasses(String[] sentence, String[] tags); Sequence[] topKLemmaClasses(String[] sentence, String[] tags, double minSequenceScore); static final int LEMMA_NUMBER; static final int DEFAULT_BEAM_SIZE; }