Java ParserModel类代码示例

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
@Override
public void doInitialize(final UimaContext aContext) throws ResourceInitializationException {
	try {
		parserChunkingModel.loadModel(ParserModel.class, getClass().getResourceAsStream("en-parser-chunking.bin"));
	} catch (final BaleenException be) {
		getMonitor().error("Unable to load OpenNLP Language Models", be);
		throw new ResourceInitializationException(be);
	}

	try {
		parser = ParserFactory.create((ParserModel) parserChunkingModel.getModel());

	} catch (final Exception e) {
		getMonitor().error("Unable to create OpenNLP parser", e);
		throw new ResourceInitializationException(e);
	}
}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
@Override
public void doInitialize(final UimaContext aContext) throws ResourceInitializationException {
	try {
		parserChunkingModel.loadModel(ParserModel.class, getClass().getResourceAsStream("en_parser_chunking.bin"));
	} catch (final BaleenException be) {
		getMonitor().error("Unable to load OpenNLP Language Models", be);
		throw new ResourceInitializationException(be);
	}

	try {
		parser = ParserFactory.create((ParserModel) parserChunkingModel.getModel());

	} catch (final Exception e) {
		getMonitor().error("Unable to create OpenNLP parser", e);
		throw new ResourceInitializationException(e);
	}
}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
@SuppressWarnings("unchecked")
@Override
public void initialize(UimaContext ctx) throws ResourceInitializationException {
  super.initialize(ctx);

  inputTypesHelper = InitializableFactory.create(
      ctx,
      inputTypesHelperClassName,
      InputTypesHelper.class);

  try {
    InputStream modelInputStream = IoUtil.getInputStream(ParserAnnotator.class, parserModelPath);
    ParserModel parserModel = new ParserModel(modelInputStream);
    if (useTagsFromCas) {
      this.casTagger = new CasPosTagger<TOKEN_TYPE, SENTENCE_TYPE>(inputTypesHelper);
      this.parser = new Parser(parserModel, beamSize, advancePercentage, casTagger);
    } else {
      this.parser = new Parser(parserModel, beamSize, advancePercentage);
    }
  } catch (IOException e) {
    throw new ResourceInitializationException(e);
  }
}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
public double scoreStructure(String ca, String q, String passage, boolean verbose) throws InvalidFormatException, IOException{
	POSTaggerME parserModel = new POSTaggerME(new POSModel(new FileInputStream(new File("en-pos-model.bin"))));
	Tokenizer tokenizer = new TokenizerME(new TokenizerModel(new FileInputStream(new File("en-token.bin"))));
	Parser parser = ParserFactory.create(new ParserModel(new FileInputStream(new File("en-parser.bin"))));
	double score = 0;
	
	Parse[] questionParse = ParserTool.parseLine(q, parser, 1);
	Parse[] passageParse = ParserTool.parseLine(q, parser, 1);
	
	if (passage.contains(ca)) {
		for (int i =0; i < questionParse.length; i++) {
			score += matchChildren(questionParse[i],passageParse[i]);
		}
	}
	
	return score;
}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
private final ParserModel loadModel(final String lang, final String model) {
  final long lStartTime = new Date().getTime();
  try {
    synchronized (parseModels) {
      if (!parseModels.containsKey(lang)) {
        parseModels.put(lang, new ParserModel(new FileInputStream(model)));
      }
    }
  } catch (final IOException e) {
    e.printStackTrace();
  }
  final long lEndTime = new Date().getTime();
  final long difference = lEndTime - lStartTime;
  System.err.println("ixa-pipe-parse model loaded in: " + difference
      + " miliseconds ... [DONE]");
  return parseModels.get(lang);
}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
public EnglishIndexer() throws Exception {
      mDicts = new EnglishDictionaries();
      mBeamSize = ConfigurationManager.getConfiguration().getInt("BeamSize");
      InputStream modelStream = null;

      modelStream = getClass().getResourceAsStream("/opennlp15model-sa/en-sent.bin");
SentenceModel model = new SentenceModel(modelStream);
mSentenceDetector = new SentenceDetectorME(model);
modelStream.close();

modelStream = getClass().getResourceAsStream("/opennlp15model-sa/en-token.bin");
mTokenizer = new EnglishTokenizer(modelStream, mDicts);
modelStream.close();

// The parser model is about 15x the size of chunking model. 
// Keep this in mind when using Deep Parsing.
modelStream = getClass().getResourceAsStream("/opennlp15model-sa/en-pos-maxent.bin");
//POSModel posModel = POSTaggerUtils.createPOSModel(modelStream);
POSModel posModel = new POSModel(modelStream);
mTagDictionary = posModel.getTagDictionary();
mPosTagger = new POSTaggerME(posModel);
modelStream.close();

modelStream = getClass().getResourceAsStream("/opennlp15model-sa/en-chunker.bin");
ChunkerModel chunkerModel = new ChunkerModel(modelStream);
mChunker = new ChunkerME(chunkerModel);
modelStream.close();

modelStream = getClass().getResourceAsStream("/opennlp15model-sa/en-parser-chunking.bin");
ParserModel parserModel = new ParserModel(modelStream);
mParser = ParserFactory.create(parserModel);
modelStream.close();

  }
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
private void loadResource() throws InvalidFormatException, IOException {
	if (parser == null) {
		InputStream is = OpenNLPParser.class.getClassLoader().getResourceAsStream(PARSER_MODEL);
		ParserModel model = new ParserModel(is);
		parser = ParserFactory.create(model);
		is.close();
	}

}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
public static Parse parse(String input) {
    ParserModel model = (ParserModel) models.get(ParserModel.class);
    Parser parser = ParserFactory.create(model);
    Parse topParses[] = ParserTool.parseLine(input, parser, tokenizer(), 1);
    return topParses[0];

}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
public OpenNLP() throws Exception {
	tagger = new POSTaggerME(new POSModel(this.getClass().getClassLoader()
			.getResourceAsStream("models/en-pos-maxent.bin")));
	parser = ParserFactory.create(new ParserModel(this.getClass().getClassLoader()
			.getResourceAsStream("models/en-parser-chunking.bin")));
	tokenizer = new TokenizerME(new TokenizerModel(this.getClass().getClassLoader()
			.getResourceAsStream("models/en-token.bin")));
	stemmer = new EnglishStemmer();
	log.info("OpenNLP models loaded");
}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
public ParserExtractor() {
	sentenceDetector = new SentenceDetector(Consts.EN_SENT_MODEL);
	
	try (InputStream modelIn = ParserExtractor.class.getClassLoader()
			.getResourceAsStream(Consts.EN_PARSER_MODEL);){
		ParserModel model = new ParserModel(modelIn);
		parser = ParserFactory.create(model);
	} catch (IOException e) {
		e.printStackTrace();
	}
}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
public void init() throws InvalidFormatException{
	File modelsDir = new File(this.modelsPath);

	this.parserMFile = new File(modelsDir, "en-parser-chunking.bin");
	this.sentDetectorMFile = new File(modelsDir, "en-sent.bin");
	this.posMFile = new File(modelsDir,"en-pos-maxent.bin");

	InputStream sentModelIn = null;
	FileInputStream parserStream;
	try {
		//for finding sentences
		sentModelIn = new FileInputStream(sentDetectorMFile);
		this.sentenceModel = new SentenceModel(sentModelIn);
		//for finding POS
		FileInputStream posModelStream = new FileInputStream(posMFile);
		POSModel model = new POSModel(posModelStream);
		this.tagger = new POSTaggerME(model);
		//for parsing
		parserStream = new FileInputStream(parserMFile);
		this.parserModel = new ParserModel(parserStream);
	} catch (FileNotFoundException e2) {
		e2.printStackTrace();
	} catch (IOException e) {
		e.printStackTrace();
	}
	this.modelsAreInitialized=true;
}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
public void init() throws InvalidFormatException{
	File modelsDir = new File(this.modelsPath);

	this.parserMFile = new File(modelsDir, "en-parser-chunking.bin");
	this.sentDetectorMFile = new File(modelsDir, "en-sent.bin");
	this.chunkerMFile=new File(modelsDir,"en-chunker.bin");
	this.posMFile = new File(modelsDir,"en-pos-maxent.bin");

	InputStream sentModelIn = null;
	FileInputStream parserStream;
	try {
		//for finding sentences
		sentModelIn = new FileInputStream(sentDetectorMFile);
		this.sentenceModel = new SentenceModel(sentModelIn);
		//for finding POS
		FileInputStream posModelStream = new FileInputStream(posMFile);
		POSModel model = new POSModel(posModelStream);
		this.tagger = new POSTaggerME(model);
		//for parsing
		parserStream = new FileInputStream(parserMFile);
		this.parserModel = new ParserModel(parserStream);
	} catch (FileNotFoundException e2) {
		// TODO Auto-generated catch block
		e2.printStackTrace();
	} catch (IOException e) {
		// TODO Auto-generated catch block
		e.printStackTrace();
	}
	this.modelsAreInitialized=true;
}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
public SentenceSimilarity() {
	File modelsDir = new File(this.modelsPath);

	this.parserMFile = new File(modelsDir, "en-parser-chunking.bin");
	this.sentDetectorMFile = new File(modelsDir, "en-sent.bin");
	this.posMFile = new File(modelsDir,"en-pos-maxent.bin");

	InputStream sentModelIn = null;
	FileInputStream parserStream;
	try {
		//for finding sentences
		sentModelIn = new FileInputStream(sentDetectorMFile);
		this.sentenceModel = new SentenceModel(sentModelIn);
		//for finding POS
		FileInputStream posModelStream = new FileInputStream(posMFile);
		POSModel model = new POSModel(posModelStream);
		this.tagger = new POSTaggerME(model);
		//for parsing
		parserStream = new FileInputStream(parserMFile);
		this.parserModel = new ParserModel(parserStream);
	} catch (FileNotFoundException e2) {
		// TODO Auto-generated catch block
		e2.printStackTrace();
	} catch (IOException e) {
		// TODO Auto-generated catch block
		e.printStackTrace();
	}
	
	sentenceDetector = new SentenceDetectorME(this.sentenceModel);
	parser = ParserFactory.create(
			this.parserModel,
			20, // beam size
			0.95); // advance percentage
}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
public void init() throws InvalidFormatException{
	File modelsDir = new File(this.modelsPath);

	this.parserMFile = new File(modelsDir, "en-parser-chunking.bin");
	this.sentDetectorMFile = new File(modelsDir, "en-sent.bin");
	this.posMFile = new File(modelsDir,"en-pos-maxent.bin");
	this.nerMFile = new File(modelsDir,"en-ner-person.bin");
	

	InputStream sentModelIn = null;
	InputStream nerModelIn = null;
	
	
	FileInputStream parserStream;
	try {
		//for finding sentences
		sentModelIn = new FileInputStream(sentDetectorMFile);
		this.sentenceModel = new SentenceModel(sentModelIn);
		//for finding POS
		FileInputStream posModelStream = new FileInputStream(posMFile);
		POSModel model = new POSModel(posModelStream);
		this.tagger = new POSTaggerME(model);
		//for parsing
		parserStream = new FileInputStream(parserMFile);
		this.parserModel = new ParserModel(parserStream);
		
		nerModelIn = new FileInputStream(nerMFile);
		this.nerModel = new TokenNameFinderModel(nerModelIn);
		
	} catch (FileNotFoundException e2) {
		// TODO Auto-generated catch block
		e2.printStackTrace();
	} catch (IOException e) {
		// TODO Auto-generated catch block
		e.printStackTrace();
	}
	this.modelsAreInitialized=true;
}
 

import opennlp.tools.parser.ParserModel; //导入依赖的package包/类
public static void init() throws InvalidFormatException {
	File modelsDir = new File(modelsPath);

	parserMFile = new File(modelsDir, "en-parser-chunking.bin");
	sentDetectorMFile = new File(modelsDir, "en-sent.bin");
	posMFile = new File(modelsDir, "en-pos-maxent.bin");

	InputStream sentModelIn = null;
	FileInputStream parserStream;
	try {
		// for finding sentences
		sentModelIn = new FileInputStream(sentDetectorMFile);
		sentenceModel = new SentenceModel(sentModelIn);
		// for finding POS
		FileInputStream posModelStream = new FileInputStream(posMFile);
		POSModel model = new POSModel(posModelStream);
		tagger = new POSTaggerME(model);
		// for parsing
		parserStream = new FileInputStream(parserMFile);
		parserModel = new ParserModel(parserStream);
	} catch (FileNotFoundException e2) {
		// TODO Auto-generated catch block
		e2.printStackTrace();
	} catch (IOException e) {
		// TODO Auto-generated catch block
		e.printStackTrace();
	}

}