Package opennlp.tools.tokenize

Examples of opennlp.tools.tokenize.Tokenizer


          new FileInputStream(
              new File(modelDir, "en-ner-" + names[mi] + ".bin")
          )));
    }

    Tokenizer tokenizer = SimpleTokenizer.INSTANCE; //<co id="co.opennlp.name.2"/>
    for (int si = 0; si < sentences.length; si++) { //<co id="co.opennlp.name.3"/>
      List<Annotation> allAnnotations = new ArrayList<Annotation>();
      String[] tokens = tokenizer.tokenize(sentences[si]);//<co id="co.opennlp.name.4"/>
      for (int fi = 0; fi < finders.length; fi++) { //<co id="co.opennlp.name.5"/>
        Span[] spans = finders[fi].find(tokens); //<co id="co.opennlp.name.6"/>
        double[] probs = finders[fi].probs(spans); //<co id="co.opennlp.name.7"/>
        for (int ni = 0; ni < spans.length; ni++) {
          allAnnotations.add( //<co id="co.opennlp.name.8"/>
View Full Code Here


   
    NameFinderME finder = new NameFinderME//<co id="co.opennlp.name.initmodel"/>
      new TokenNameFinderModel(new FileInputStream(getPersonModel()))
    );
   
    Tokenizer tokenizer = SimpleTokenizer.INSTANCE; //<co id="co.opennlp.name.inittokenizer2"/>
   
    for (int si = 0; si < sentences.length; si++) {
      String[] tokens = tokenizer.tokenize(sentences[si]); //<co id="co.opennlp.name.tokenize2"/>
      Span[] names = finder.find(tokens); //<co id="co.opennlp.name.findnames3"/>
      displayNames(names, tokens);
    }
   
    finder.clearAdaptiveData(); //<co id="co.opennlp.name.clear"/>
    /*<calloutlist>
    <callout arearefs="co.opennlp.name.initmodel">
      <para>Initialize a new model for identifying people names based on the
        binary compressed model in the file "en-ner-person.bin".</para>
    </callout>
    <callout arearefs="co.opennlp.name.inittokenizer2">
      <para>Initialize a tokenizer to split the sentence into individual words
        and symbols.</para>
    </callout>
    <callout arearefs="co.opennlp.name.tokenize2">
      <para>Split the sentence into an array of tokens.</para>
    </callout>
    <callout arearefs="co.opennlp.name.findnames3">
      <para>Identify the names in the sentence and return token-based offsets
      to these names.</para>
    </callout>
    <callout arearefs="co.opennlp.name.clear">
      <para>Clear data structures that store which words have been seen
      previously in the document and whether these words were considered part
      of a person's name.</para>
    </callout>   
    </calloutlist>*/
    //<end id="ne-setup"/>

    //<start id="ne-display2"/>
    for (int si = 0; si < sentences.length; si++) { //<co id="co.opennlp.name.eachsent2"/>
      Span[] tokenSpans = tokenizer.tokenizePos(sentences[si]); //<co id="co.opennlp.name.tokenizepos"/>
      String[] tokens = Span.spansToStrings(tokenSpans, sentences[si]); //<co id="co.opennlp.name.convert2strings"/>
      Span[] names = finder.find(tokens); //<co id="co.opennlp.name.findnames4"/>

      for (int ni = 0; ni < names.length; ni++) {
        Span startSpan = tokenSpans[names[ni].getStart()]; //<co id="co.opennlp.name.computestart"/>
        int nameStart  = startSpan.getStart();
       
        Span endSpan   = tokenSpans[names[ni].getEnd() - 1]; //<co id="co.opennlp.name.computeend"/>
        int nameEnd    = endSpan.getEnd();
       
        String name = sentences[si].substring(nameStart, nameEnd); //<co id="co.opennlp.name.namestring"/>
        System.out.println(name);
      }
    }
    /*<calloutlist>
    <callout arearefs="co.opennlp.name.eachsent2">
      <para>Iterate over each sentence.</para>
    </callout>
    <callout arearefs="co.opennlp.name.tokenizepos">
      <para>Split the sentence into an array of tokens and return the
        character offsets (spans) of those tokens.</para>
    </callout>
    <callout arearefs="co.opennlp.name.findnames4">
      <para>
      Identify the names in the sentence and return token-based offsets to these names.
      </para>
    </callout>
    <callout arearefs="co.opennlp.name.computestart">
      <para>
      Compute the start character index of the name.
      </para>
    </callout>   
    <callout arearefs="co.opennlp.name.computeend">
      <para>
      Compute the end character index (last character +1) of the name.
      </para>
    </callout>
    <callout arearefs="co.opennlp.name.computeend">
      <para>
      Compute the string which represents the name.
      </para>
    </callout>
    </calloutlist>*/
    //<end id="ne-display2"/>
    //<start id="ne-prob"/>
    for (int si = 0; si < sentences.length; si++) {//<co id="co.opennlp.name.eachsent3"/>
      String[] tokens = tokenizer.tokenize(sentences[si]); //<co id="co.opennlp.name.tokenize3"/>
      Span[] names = finder.find(tokens); //<co id="co.opennlp.name.findnames1"/>
      double[] spanProbs = finder.probs(names); //<co id="co.opennlp.name.probs"/>
    }
    /*<calloutlist>
    <callout arearefs="co.opennlp.name.eachsent3"><para>Iterate over each sentence.</para></callout>
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  public void train(String source, String destination) throws IOException {
    //<start id="maxent.examples.train.setup"/>
    File[] inputFiles = FileUtil.buildFileList(new File(source));
    File modelFile = new File(destination);
   
    Tokenizer tokenizer = SimpleTokenizer.INSTANCE; //<co id="tm.tok"/>
    CategoryDataStream ds = new CategoryDataStream(inputFiles, tokenizer);

    int cutoff = 5;
    int iterations = 100;
    NameFinderFeatureGenerator nffg //<co id="tm.fg"/>
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    InputStream modelStream = //<co id="tmx.modelreader"/>
        new FileInputStream(modelFile);
    DoccatModel model = new DoccatModel(modelStream);
    DocumentCategorizer categorizer //<co id="tmx.categorizer"/>
      = new DocumentCategorizerME(model, nffg, bowfg);
    Tokenizer tokenizer = SimpleTokenizer.INSTANCE;
  
    int catCount = categorizer.getNumberOfCategories();
    Collection<String> categories
      = new ArrayList<String>(catCount);
    for (int i=0; i < catCount; i++) {
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  public double[] categorize(String text[]) {
    return model.eval(mContextGenerator.getContext(text));
  }

  public double[] categorize(String documentText) {
    Tokenizer tokenizer = SimpleTokenizer.INSTANCE;
    return categorize(tokenizer.tokenize(documentText));
  }
View Full Code Here

   *
   * @param text
   */
  public SentencesToTree(String text, TokenizerModel model){
    /* Configure the tokenizer with preloaded model */
    Tokenizer tokenizer = new TokenizerME(model);
    /* tokens has an array of strings, where each string is a token */
    String s = spaces(tokenizer.tokenize(text));
    this.text = this.upperCase(s);
  }
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  public ObjectStream<NameSample> create(String[] args) {

    Parameters params = ArgumentParser.parse(args, Parameters.class);

    TokenizerModel tokenizerModel = new TokenizerModelLoader().load(params.getTokenizerModel());
    Tokenizer tokenizer = new TokenizerME(tokenizerModel);

    ObjectStream<String> mucDocStream = new FileToStringSampleStream(
        new DirectorySampleStream(params.getData(), new FileFilter() {

          public boolean accept(File file) {
View Full Code Here

  /**
   * Categorizes the given text. The text is tokenized with the SimpleTokenizer before it
   * is passed to the feature generation.
   */
  public double[] categorize(String documentText) {
    Tokenizer tokenizer = SimpleTokenizer.INSTANCE;
    return categorize(tokenizer.tokenize(documentText));
  }
View Full Code Here

   
    ParserModel parserModel = new ParserModelLoader().load(params.getParserModel());
    Parser parser =  ParserFactory.create(parserModel);
   
    TokenizerModel tokenizerModel = new TokenizerModelLoader().load(params.getTokenizerModel());
    Tokenizer tokenizer = new TokenizerME(tokenizerModel);
   
    ObjectStream<String> mucDocStream = new FileToStringSampleStream(
        new DirectorySampleStream(params.getData(), new FileFilter() {
         
          public boolean accept(File file) {
View Full Code Here

    @Test
    public void testLoadEnTokenizer() throws IOException{
        TokenizerModel model = openNLP.getTokenizerModel("en");
        Assert.assertNotNull(model);
        Tokenizer tokenizer = openNLP.getTokenizer("en");
        Assert.assertNotNull(tokenizer);
    }
View Full Code Here

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