Package opennlp.tools.parser

Examples of opennlp.tools.parser.ParserModel$ChunkerModelSerializer

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    ModelUpdaterParams params = validateAndParseParams(
        ArgumentParser.filter(args, ModelUpdaterParams.class), ModelUpdaterParams.class);
   
    // Load model to be updated
    File modelFile = params.getModel();
    ParserModel originalParserModel = new ParserModelLoader().load(modelFile);

    ObjectStreamFactory<Parse> factory = getStreamFactory(format);
    String[] fargs = ArgumentParser.filter(args, factory.getParameters());
    validateFactoryArgs(factory, fargs);
    ObjectStream<Parse> sampleStream = factory.create(fargs);
   
    ParserModel updatedParserModel;
    try {
      updatedParserModel = trainAndUpdate(originalParserModel, sampleStream, params);
    }
    catch (IOException e) {
      throw new TerminateToolException(-1, "IO error while reading training data or indexing data: "
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    if (args.length != 2) {
      System.out.println(getHelp());
    } else {
   
      File parserModelInFile = new File(args[0]);
      ParserModel parserModel = new ParserModelLoader().load(parserModelInFile);

      File taggerModelInFile = new File(args[1]);
      POSModel taggerModel = new POSModelLoader().load(taggerModelInFile);

      ParserModel updatedParserModel = parserModel.updateTaggerModel(taggerModel);

      CmdLineUtil.writeModel("parser", parserModelInFile, updatedParserModel);
    }
  }
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    Map<String, String> attachReportMap = new HashMap<String, String>();
    AbstractModel attachModel = TrainUtil.train(attachEvents, mlParams.getSettings("attach"), attachReportMap);
    opennlp.tools.parser.chunking.Parser.mergeReportIntoManifest(manifestInfoEntries, attachReportMap, "attach");
   
    // TODO: Remove cast for HeadRules
    return new ParserModel(languageCode, buildModel, checkModel,
        attachModel, posModel, chunkModel,
        (opennlp.tools.parser.lang.en.HeadRules) rules, ParserType.TREEINSERT, manifestInfoEntries);
  }
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  public ObjectStream<CorefSample> create(String[] args) {
   
    Parameters params = ArgumentParser.parse(args, Parameters.class);
   
    ParserModel parserModel = new ParserModelLoader().load(params.getParserModel());
    Parser parser =  ParserFactory.create(parserModel);
   
    TokenizerModel tokenizerModel = new TokenizerModelLoader().load(params.getTokenizerModel());
    Tokenizer tokenizer = new TokenizerME(tokenizerModel);
   
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    if (mLogger.isLoggable(Level.INFO)) {
      mLogger.log(Level.INFO, "Initializing the OpenNLP Parser.");
    }

    ParserModel model;

    try {
      ParserModelResource modelResource = (ParserModelResource) context
          .getResourceObject(UimaUtil.MODEL_PARAMETER);
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    return model;
  }

  @Override
  protected ParserModel loadModel(InputStream in) throws IOException {
    return new ParserModel(in);
  }
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    try {
      File d = new File(dataDir);

      if (!d.isDirectory()) {
        FileInputStream fis = new FileInputStream(d);
        ParserModel model = new ParserModel(fis);
        parser = new Parser(model, AbstractBottomUpParser.defaultBeamSize, AbstractBottomUpParser.defaultAdvancePercentage);
      }
    } catch (IOException e) {
      e.printStackTrace();
    }
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//    String modelFileOrDirname = (String) aContext.getConfigParameterValue("modelDir");
    try {
//      FileInputStream fis = new FileInputStream(new File(modelFileOrDirname));
//      File parserFile = FileLocator.locateFile(parserModel);
      FileInputStream fis = new FileInputStream(parserModel);
      ParserModel model = new ParserModel(fis);
//      parser = ParserFactory.create(model, AbstractBottomUpParser.defaultBeamSize, AbstractBottomUpParser.defaultAdvancePercentage); //TreebankParser.getParser(modelFileOrDirname, useTagDictionary, useCaseSensitiveTagDictionary, AbstractBottomUpParser.defaultBeamSize, AbstractBottomUpParser.defaultAdvancePercentage);
      parser = new Parser(model, AbstractBottomUpParser.defaultBeamSize, AbstractBottomUpParser.defaultAdvancePercentage);
      fis.close();
    } catch (IOException e) {
      e.printStackTrace();
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    AbstractModel checkModel = train(hskes, iterations, cut);
    manifestInfoEntries.put("Training-Checker-Eventhash",
        hskes.calculateHashSum().toString(16));
   
    // TODO: Remove cast for HeadRules
    return new ParserModel(languageCode, buildModel, checkModel,
        posModel, chunkModel, (opennlp.tools.parser.lang.en.HeadRules) rules,
        ParserType.CHUNKING, manifestInfoEntries);
  }
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    Map<String, String> attachReportMap = new HashMap<String, String>();
    MaxentModel attachModel = TrainUtil.train(attachEvents, mlParams.getSettings("attach"), attachReportMap);
    opennlp.tools.parser.chunking.Parser.mergeReportIntoManifest(manifestInfoEntries, attachReportMap, "attach");

    // TODO: Remove cast for HeadRules
    return new ParserModel(languageCode, buildModel, checkModel,
        attachModel, posModel, chunkModel,
        (opennlp.tools.parser.HeadRules) rules, ParserType.TREEINSERT, manifestInfoEntries);
  }
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Related Classes of opennlp.tools.parser.ParserModel$ChunkerModelSerializer

  • com.tamingtext.opennlp.ParserTest
  • functionality.Models
  • kpi.asoiu.parsers.ParseSentence
  • net.sf.nlpshell.Main
  • opennlp.model.AbstractModel
  • opennlp.model.BinaryFileDataReader
  • opennlp.model.GenericModelReader
  • opennlp.tools.chunker.ChunkerModel
  • opennlp.tools.cmdline.parser.ModelUpdaterTool
  • opennlp.tools.cmdline.parser.ParserEvaluatorTool
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