Package opennlp.tools.sentdetect

Examples of opennlp.tools.sentdetect.SentenceDetectorME


     * @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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    System.setProperty("wordnet.dir", "./WordNet-3.0");

    File modelFile = new File(models, "en-sent.bin");
    InputStream modelStream = new FileInputStream(modelFile);
    SentenceModel model = new SentenceModel(modelStream);
    sentenceDetector = new SentenceDetectorME(model);
    finders = new HashMap<String, NameFinderME>();
    finders.put("Names", new NameFinderME(new TokenNameFinderModel(
            new FileInputStream(getPersonModel()))));
    finders.put("Dates", new NameFinderME(new TokenNameFinderModel(
            new FileInputStream(getDateModel()))));
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    //... Setup the models
    File modelFile = new File(modelDir, "en-sent.bin");
    InputStream modelStream = new FileInputStream(modelFile);
    SentenceModel model = new SentenceModel(modelStream);
    SentenceDetector detector = //<co id="openSentDetect.co.detect"/>
      new SentenceDetectorME(model);
    String testString = "This is a sentence. It has fruits, vegetables," +
      " etc. but does not have meat. Mr. Smith went to Washington.";
    String[] result = detector.sentDetect(testString); //<co id="openSentDetect.co.run"/>
    for (int i = 0; i < result.length; i++) {
      System.out.println("Sentence: " + result[i]);
    }
    /*<calloutlist>
        <callout arearefs="openSentDetect.co.detect"><para>Create the <command>SentenceDetector</command> with the en-sent.bin model</para></callout>
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    }

    File modelFile = new File(modelDir, "en-sent.bin");
    InputStream modelStream = new FileInputStream(modelFile);
    SentenceModel model = new SentenceModel(modelStream);
    detector = new SentenceDetectorME(model);
  }
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        File.separatorChar + language + "-sent.bin";
   
    log.info("Loading sentence model {}", modelFile);
    InputStream modelStream = new FileInputStream(modelFile);
    SentenceModel model = new SentenceModel(modelStream);
    detector = new SentenceDetectorME(model);
  }
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      model = modelResource.getModel();
    } catch (ResourceAccessException e) {
      throw new ResourceInitializationException(e);
    }

    sentenceDetector = new SentenceDetectorME(model);
  }
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    }

    @SuppressWarnings("unchecked")
    @Override
    public DataBag exec(Tuple input) throws IOException {
        SentenceDetectorME sentenceDetector = new SentenceDetectorME(model);
        DataBag output = bagFactory.newDefaultBag();
        Object t0 = input.get(0);
        if (!(t0 instanceof String)) {
            throw new IOException("Expected input to be chararray, but got "
                    + t0.getClass().getName());
        }
        Object t1 = input.get(1);
        if (!(t1 instanceof DataBag)) {
            throw new IOException("Expected input to be bag of links, but got "
                    + t1.getClass().getName());
        }
        Object t2 = input.get(2);
        if (!(t1 instanceof DataBag)) {
            throw new IOException(
                    "Expected input to be bag of paragraphs, but got "
                            + t2.getClass().getName());
        }
        String text = (String) t0;
        DataBag links = (DataBag) t1;
        DataBag paragraphBag = (DataBag) t2;

        // convert the bag of links as absolute spans over the text
        List<Span> linkSpans = new ArrayList<Span>();
        for (Tuple l : links) {
            linkSpans.add(new Span((Integer) l.get(1), (Integer) l.get(2),
                    (String) l.get(0)));
        }
        Collections.sort(linkSpans);

        // iterate of the paragraph and extract sentence locations
        int order = 0;
        for (Tuple p : paragraphBag) {
            Integer beginParagraph = (Integer) p.get(1);
            Integer endParagraph = (Integer) p.get(2);
            Span[] spans = sentenceDetector.sentPosDetect(text.substring(
                    beginParagraph, endParagraph));
            for (Span sentenceRelative : spans) {
                // for each sentence found in that paragraph, compute the
                // absolute span of the text
                order++;
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      model = modelResource.getModel();
    } catch (ResourceAccessException e) {
      throw new ResourceInitializationException(e);
    }

    sentenceDetector = new SentenceDetectorME(model);
  }
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    if (params.getMisclassified()) {
      errorListener = new SentenceEvaluationErrorListener();
    }
   
    SentenceDetectorEvaluator evaluator = new SentenceDetectorEvaluator(
        new SentenceDetectorME(model), errorListener);
   
    System.out.print("Evaluating ... ");
      ObjectStream<SentenceSample> sampleStream = SentenceDetectorTrainerTool.openSampleData("Test",
          trainingDataInFile, encoding);
     
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      throw new TerminateToolException(1);
    }

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

    ObjectStream<String> paraStream =
      new ParagraphStream(new PlainTextByLineStream(new InputStreamReader(System.in)));
   
    PerformanceMonitor perfMon = new PerformanceMonitor(System.err, "sent");
    perfMon.start();
   
    try {
      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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