Examples of opennlp.maxent.PlainTextByLineDataStream

opennlp.maxent.PlainTextByLineDataStream
This DataStream implementation will take care of reading a plain text file and returning the Strings between each new line character, which is what many Maxent applications need in order to create EventStreams.

      predictor.eval("Blarmey");
  }
  else {
      try {
    DataStream ds =
        new PlainTextByLineDataStream(
      new FileReader(new File(dataFileName)));


    while (ds.hasNext()) {
        String s = (String)ds.nextToken();
        predictor.eval(s.substring(0, s.lastIndexOf(' ')),real);
    }
    return;
      }
      catch (Exception e) {

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        + "Model.txt";
      try {
        FileReader datafr = new FileReader(new File(dataFileName));
        EventStream es;
        if (!real) { 
          es = new BasicEventStream(new PlainTextByLineDataStream(datafr));
        }
        else {
          es = new RealBasicEventStream(new PlainTextByLineDataStream(datafr));
        }
        GIS.SMOOTHING_OBSERVATION = SMOOTHING_OBSERVATION;
        AbstractModel model;
        if (type.equals("maxent")) {

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      }
      File inFile = new File(args[ai++]);
      File outFile = new File(args[ai++]);
      GISModel mod;


      EventStream es = new NameFinderEventStream(new PlainTextByLineDataStream(new InputStreamReader(new FileInputStream(inFile),encoding)));
      if (args.length > ai)
        mod = train(es, Integer.parseInt(args[ai++]), Integer.parseInt(args[ai++]));
      else
        mod = train(es, 100, 5);

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        }
        return (null != head);
    }
    
    public static void main(String[] args) {
      EventStream es =  new SDEventStream(new PlainTextByLineDataStream(new InputStreamReader(System.in)));
      while(es.hasNext()) {
        System.out.println(es.nextEvent());
      }
    }

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    EventStream es;
    DataStream ds;
    Reader reader;


    reader = new BufferedReader(new FileReader(inFile));
    ds = new PlainTextByLineDataStream(reader);
    es = new SDEventStream(ds, scanner);
    return GIS.trainModel(es, iterations, cut);
  }

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    File inFile = new File(args[ai++]);
    File outFile = new File(args[ai++]);
    GISModel mod;
    
    try {
      EventStream es = new SDEventStream(new PlainTextByLineDataStream(new InputStreamReader(new FileInputStream(inFile),encoding)));


      if (args.length > ai)
        mod = train(es, Integer.parseInt(args[ai++]), Integer.parseInt(args[ai++]));
      else
        mod = train(es, 100, 5);

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        mdict.persist(new File(dict));
      }
      EventStream es;
      if (encoding == null) {
        if (dict == null) {
          es = new POSEventStream(new PlainTextByLineDataStream(new InputStreamReader(new FileInputStream(inFile))));
        }
        else {
          es = new POSEventStream(new PlainTextByLineDataStream(new InputStreamReader(new FileInputStream(inFile))), new Dictionary(dict));
        }
      }
      else {
        if (dict == null) {
          es = new POSEventStream(new PlainTextByLineDataStream(new InputStreamReader(new FileInputStream(inFile),encoding)));
        }
        else {
          es = new POSEventStream(new PlainTextByLineDataStream(new InputStreamReader(new FileInputStream(inFile),encoding)), new Dictionary(dict));
        }
      }
      mod = train(es, iterations, cutoff);
      System.out.println("Saving the model as: " + outFile);
      new SuffixSensitiveGISModelWriter(mod, outFile).persist();

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      AbstractModelWriter writer = null;
      try {
        FileReader datafr = new FileReader(new File(dataFileName));
        EventStream es;
        if (!real) { 
          es = new BasicEventStream(new PlainTextByLineDataStream(datafr));
        }
        else {
          es = new RealBasicEventStream(new PlainTextByLineDataStream(datafr));
        }
        GIS.SMOOTHING_OBSERVATION = SMOOTHING_OBSERVATION;
        AbstractModel model;
        if (type.equals("maxent")) {

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Related Classes of opennlp.maxent.PlainTextByLineDataStream

CreateModel

opennlp.tools.namefind.NameFinderME

opennlp.tools.postag.POSTaggerME

opennlp.tools.sentdetect.SDEventStream

opennlp.tools.sentdetect.SentenceDetectorME

Predict

java.io.BufferedReader

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