Package com.tamingtext.qa

Examples of com.tamingtext.qa.ChunkParser

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    ChunkerME chunker = new ChunkerME(chunkerModel);
    FileInputStream posStream = new FileInputStream(
        new File(modelDir,"en-pos-maxent.bin"));
    POSModel posModel = new POSModel(posStream);
    POSTaggerME tagger =  new POSTaggerME(posModel);
    Parser parser = new ChunkParser(chunker, tagger);
    Parse[] results = ParserTool.parseLine("Who is the president of egypt ?", parser, 1);
    String[] context = atcg.getContext(results[0]);
    List<String> features = Arrays.asList(context);
    assertTrue(features.contains("qw=who"));
    assertTrue(features.contains("hw=president"));
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    ChunkerME chunker = new ChunkerME(chunkerModel);
    InputStream posStream = new FileInputStream(
            new File(modelDir,"en-pos-maxent.bin"));
    POSModel posModel = new POSModel(posStream);
    POSTaggerME tagger =  new POSTaggerME(posModel);
    Parser parser = new ChunkParser(chunker, tagger);
    //<start id="att.answerTypeDemo"/>
    AnswerTypeContextGenerator atcg =
            new AnswerTypeContextGenerator(
                    new File(getWordNetDictionary().getAbsolutePath()));
    InputStream is = Thread.currentThread().getContextClassLoader()
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    ChunkerME chunker = new ChunkerME(chunkerModel);
    FileInputStream posStream = new FileInputStream(
        new File(modelDir,"en-pos-maxent.bin"));
    POSModel posModel = new POSModel(posStream);
    POSTaggerME tagger =  new POSTaggerME(posModel);
    Parser parser = new ChunkParser(chunker, tagger);
    Parse[] results = ParserTool.parseLine("The Minnesota Twins , " +
            "the 1991 World Series Champions , are currently in third place .",
            parser, 1);
    Parse p = results[0];
    Parse[] chunks = p.getChildren();
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Related Classes of com.tamingtext.qa.ChunkParser

  • com.tamingtext.opennlp.AnswerTypeTest
  • com.tamingtext.opennlp.ChunkParserTest
  • opennlp.tools.parser.Parse
  • opennlp.tools.util.Span
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