Package opennlp.tools.sentdetect

Examples of opennlp.tools.sentdetect.SentenceDetectorME

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                getResourceAsStream(chunkerModelFile)));
    }

    public static SentenceDetector getDefaultSentenceDetector()
            throws IOException {
        return new SentenceDetectorME(new SentenceModel(
                getResourceAsStream(sentDetectorModelFile)));
    }
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        this.name = n;
    }

    protected List<SurfaceFormOccurrence> extractNameOccurrences(BaseModel nameFinderModel, Text text, URI oType) {
        String intext = text.text();
        SentenceDetectorME sentenceDetector = new SentenceDetectorME((SentenceModel)sentenceModel);
        String[] sentences = sentenceDetector.sentDetect(intext);
        Span[] sentenceEndings = sentenceDetector.sentPosDetect(intext);
        int[] sentencePositions = new int[sentences.length + 1];
        for (int k=0; k<sentenceEndings.length; k++) {
            sentencePositions[k] = sentenceEndings[k].getStart();
        }
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   */
  protected List<SurfaceFormOccurrence> extractNPNGrams(Text text) {
        String intext = text.text();
    //System.out.println("\n\nRR- nextractNPNGrams(...) method called! with text: " + intext + "\n\n");
    List<SurfaceFormOccurrence> npNgramSFLst = new ArrayList<SurfaceFormOccurrence>();
    SentenceDetectorME  sentenceDetector = new SentenceDetectorME((SentenceModel)sentenceModel);
    TokenizerME tokenizer = new TokenizerME((TokenizerModel)tokenModel);
    POSTaggerME posTagger = new POSTaggerME((POSModel)posModel);
    ChunkerME chunker = new ChunkerME((ChunkerModel)chunkModel);

    Span[] sentSpans = sentenceDetector.sentPosDetect(intext);
    for (Span sentSpan : sentSpans) {
      String sentence = sentSpan.getCoveredText(intext).toString();
      int start = sentSpan.getStart();
      Span[] tokSpans = tokenizer.tokenizePos(sentence);
      String[] tokens = new String[tokSpans.length];
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     * @throws IOException
     */
    public ApacheExtractor() throws IOException {
        nameFinder = new NameFinderME(new TokenNameFinderModel(ApacheExtractor.class.getResourceAsStream(pathToNERModel)));
        tokenizer = new TokenizerME(new TokenizerModel(ApacheExtractor.class.getResourceAsStream(pathToTokenizerModel)));
        sentenceDetector = new SentenceDetectorME(new SentenceModel(ApacheExtractor.class.getResourceAsStream(pathToSentenceDetectorModel)));
    }
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        // version with explicit sentence endings to reflect heading / paragraph
        // structure of an HTML or PDF document converted to text
        String textWithDots = text.replaceAll("\\n\\n", ".\n");
        text = removeNonUtf8CompliantCharacters(text);

        SentenceDetectorME sentenceDetector = new SentenceDetectorME(getSentenceModel("en"));

        Span[] sentenceSpans = sentenceDetector.sentPosDetect(textWithDots);

        NameFinderME finder = new NameFinderME(nameFinderModel);
        Tokenizer tokenizer = openNLP.getTokenizer(language);
        Map<String,List<NameOccurrence>> nameOccurrences = new LinkedHashMap<String,List<NameOccurrence>>();
        for (int i = 0; i < sentenceSpans.length; i++) {
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        if(model != null) {
            log.debug("Sentence Detection Model {} for lanugage '{}' version: {}",
                new Object[]{model.getClass().getSimpleName(),
                             model.getLanguage(),
                             model.getVersion() != null ? model.getVersion() : "undefined"});
            return new SentenceDetectorME(model);
        }
        log.debug("Sentence Detection Model for Language '{}' not available.", language);
        return null;
    }
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      System.out.println(getHelp());
    } else {

      SentenceModel model = new SentenceModelLoader().load(new File(args[0]));

      SentenceDetectorME sdetector = new SentenceDetectorME(model);

      PerformanceMonitor perfMon = new PerformanceMonitor(System.err, "sent");
      perfMon.start();

      try {
        ObjectStream<String> paraStream = new ParagraphStream(new PlainTextByLineStream(new SystemInputStreamFactory(),
            SystemInputStreamFactory.encoding()));

        String para;
        while ((para = paraStream.read()) != null) {

          String[] sents = sdetector.sentDetect(para);
          for (String sentence : sents) {
            System.out.println(sentence);
          }

          perfMon.incrementCounter(sents.length);
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    if (params.getMisclassified()) {
      errorListener = new SentenceEvaluationErrorListener();
    }

    SentenceDetectorEvaluator evaluator = new SentenceDetectorEvaluator(
        new SentenceDetectorME(model), errorListener);

    System.out.print("Evaluating ... ");
    try {
    evaluator.evaluate(sampleStream);
    }
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    SentenceDetector sentDetector;

    if (params.getSentenceDetectorModel() != null) {
      try {
        sentDetector = new SentenceDetectorME(new SentenceModel(params.getSentenceDetectorModel()));
      } catch (IOException e) {
        throw new TerminateToolException(-1, "Failed to load sentence detector model!", e);
      }
    }
    else {
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  protected BratNameSampleStream(SentenceModel sentModel, TokenizerModel tokenModel,
      ObjectStream<BratDocument> samples) {
    super(samples);

    // TODO: We can pass in custom validators here ...
    this.sentDetector = new SentenceDetectorME(sentModel);
    this.tokenizer = new TokenizerME(tokenModel);
  }
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Related Classes of opennlp.tools.sentdetect.SentenceDetectorME

  • com.bericotech.clavin.extractor.ApacheExtractor
  • com.tamingtext.frankenstein.Frankenstein
  • com.tamingtext.sentences.SentenceDetectionTest
  • com.tamingtext.texttamer.solr.NameFilterTest
  • com.tamingtext.util.SentenceDetectorFactory
  • edu.washington.cs.knowitall.util.DefaultObjects
  • functionality.SentenceOnText
  • gate.opennlp.OpenNlpSentenceSplit
  • ivory.lsh.bitext.PreprocessHelper
  • kpi.asoiu.parsers.ParseText
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