Examples of opennlp.tools.namefind.TokenNameFinderModel$FeatureGeneratorCreationError

opennlp.tools.namefind.TokenNameFinderModel
The {@link TokenNameFinderModel} is the model usedby a learnable {@link TokenNameFinder}. @see NameFinderME

     * Name Finder and Tokenizer.
     * 
     * @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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                new Path(pathPrefix + "/en-ner-organization.bin"),
                new Path(pathPrefix + "/en-ner-person.bin")};
        List<TokenNameFinder> finders = new ArrayList<TokenNameFinder>();
        for (Path finderHdfsPath : finderHdfsPaths) {
            InputStream finderModelInputStream = fs.open(finderHdfsPath);
            TokenNameFinderModel model = null;
            try {
                model = new TokenNameFinderModel(finderModelInputStream);
            } finally {
                finderModelInputStream.close();
            }
            NameFinderME finder = new NameFinderME(model);
            finders.add(finder);

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    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()))));
    finders.put("Locations", new NameFinderME(new TokenNameFinderModel(
            new FileInputStream(getLocationModel()))));


    tokenizer = SimpleTokenizer.INSTANCE;
  }

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    File modelDir = getModelDir();
     
    finder = new NameFinderME[modelName.length];
    for (int i=0; i < modelName.length; i++) {
      finder[i] = new NameFinderME(new TokenNameFinderModel(
          new FileInputStream(
              new File(modelDir, "en-ner-" + modelName[i] + ".bin")
              )));
    }

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              "said Joanne " +
      "Drake, chief of staff for the Reagan Foundation."};
    NameFinderME[] finders = new NameFinderME[3];
    String[] names = {"person", "location", "date"};
    for (int mi = 0; mi < names.length; mi++) {  //<co id="co.opennlp.name.1"/>
      finders[mi] = new NameFinderME(new TokenNameFinderModel(
          new FileInputStream(
              new File(modelDir, "en-ner-" + names[mi] + ".bin")
          )));
    }

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    String taggedSent = 
      "<START:person> Britney Spears <END> was reunited " +
      "with her sons <START:date> Saturday <END> ";
    ObjectStream<NameSample> nss = new NameSampleDataStream(
        new PlainTextByLineStream(new StringReader(taggedSent)));
    TokenNameFinderModel model = NameFinderME.train( 
        "en", 
        "default" ,
        nss, 
        (AdaptiveFeatureGenerator) null,
        Collections.<String,Object>emptyMap(),
        70 , 1 );
    
    File outFile = new File(destDir,"multi-custom.bin");
    FileOutputStream outFileStream = new FileOutputStream(outFile);
    model.serialize(outFileStream); 
    
    NameFinderME nameFinder = new NameFinderME(model);
    
    String[] tokens = 
        (" Britney Spears was reunited with her sons Saturday .")

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    //String[] names = {"person"};
    //String[] names = {"date","location","money","organization","percentage","person","time"};
    String[] names = {"person","location","date"};
    NameFinderME[] finders = new NameFinderME[names.length];
    for (int mi = 0; mi < names.length; mi++) {
      finders[mi] = new NameFinderME(new TokenNameFinderModel(
          new FileInputStream(
              new File(modelDir, "en-ner-" + names[mi] + ".bin")
              )));
    }
    memStatus.dumpMemory("after non-pooled model load of " + Arrays.toString(names));

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      new PlainTextByLineStream(
        new java.io.FileReader(inFile)));


    int iterations = 100;
    int cutoff = 5;
    TokenNameFinderModel model = NameFinderME.train( //<co id="co.opennlp.name.train"/>
        "en", // language
        "person", // type
        nss, 
        (AdaptiveFeatureGenerator) null,
        Collections.<String,Object>emptyMap(),
        iterations,
        cutoff);
    
    File outFile = new File(destDir, "person-custom.bin");
    FileOutputStream outFileStream = new FileOutputStream(outFile);
    model.serialize(outFileStream); //<co id="co.opennlp.name.persist3"/>
    /*<calloutlist>
    <callout arearefs="co.opennlp.name.initnamestream"><para>Create a stream of name samples based on annotated data in the "person.train" file.</para></callout>
    <callout arearefs="co.opennlp.name.train"><para>Train the model.</para></callout>
    <callout arearefs="co.opennlp.name.persist3"><para>Save the model to a file.</para></callout>
    </calloutlist>*/

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      new PlainTextByLineStream(
        new java.io.FileReader(inFile)));


    int iterations = 100;
    int cutoff = 5;
    TokenNameFinderModel model = NameFinderME.train( //<co id="co.opennlp.name.train2"/>
        "en", // language
        "person", // type
        nss, 
        featureGenerators, 
        Collections.<String,Object>emptyMap(),
        iterations, 
        cutoff);


    File outFile = new File(destDir,"person-custom2.bin");
    FileOutputStream outFileStream = new FileOutputStream(outFile);
    model.serialize(outFileStream); //<co id="co.opennlp.name.persist2"/>
    /*<calloutlist>
   <callout arearefs="co.opennlp.name.initfeat"><para>Create the sample stream..</para></callout>
   <callout arearefs="co.opennlp.name.train2"><para>Train the model with a custom feature generator.</para></callout>
   <callout arearefs="co.opennlp.name.persist2"><para>Save the model to a file.</para></callout>
   </calloutlist>*/
    //<end id="ne-features-train"/>
    
    //<start id="ne-features-test"/>
    NameFinderME finder = new NameFinderME(
        new TokenNameFinderModel(
            new FileInputStream(
                new File(destDir, "person-custom2.bin")
                )), featureGenerators, NameFinderME.DEFAULT_BEAM_SIZE);
    //<end id="ne-features-test"/>
  }

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      "observation at a hospital in Santa Monica, California, " +
              "said Joanne " +
      "Drake, chief of staff for the Reagan Foundation."};
    
    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++) {

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