本文整理汇总了Java中dragon.nlp.tool.Lemmatiser类的典型用法代码示例。如果您正苦于以下问题：Java Lemmatiser类的具体用法？Java Lemmatiser怎么用？Java Lemmatiser使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
Lemmatiser类属于dragon.nlp.tool包，在下文中一共展示了Lemmatiser类的8个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Java代码示例。
示例1: String2TokenSequencePipe
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import dragon.nlp.tool.Lemmatiser; //导入依赖的package包/类
public String2TokenSequencePipe(Lemmatiser lemmatiser, Tagger posTagger, boolean useNumericNormalization, banner.tagging.Tagger preTagger)
{
super(null, LabelAlphabet.class);
this.lemmatiser = lemmatiser;
this.posTagger = posTagger;
this.useNumericNormalization = useNumericNormalization;
this.preTagger = preTagger;
}
开发者ID:clulab，
项目名称:reach-banner，
代码行数:9，
代码来源:String2TokenSequencePipe.java
示例2: String2TokenSequencePipe
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import dragon.nlp.tool.Lemmatiser; //导入依赖的package包/类
public String2TokenSequencePipe(Lemmatiser lemmatiser, Tagger posTagger, boolean useNumericNormalization)
{
super(null, LabelAlphabet.class);
this.lemmatiser = lemmatiser;
this.posTagger = posTagger;
this.useNumericNormalization = useNumericNormalization;
}
开发者ID:leebird，
项目名称:legonlp，
代码行数:8，
代码来源:String2TokenSequencePipe.java
示例3: setLemmatiser
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import dragon.nlp.tool.Lemmatiser; //导入依赖的package包/类
public void setLemmatiser(Lemmatiser lemmatiser)
{
this.lemmatiser = lemmatiser;
}
开发者ID:clulab，
项目名称:reach-banner，
代码行数:5，
代码来源:String2TokenSequencePipe.java
示例4: train
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import dragon.nlp.tool.Lemmatiser; //导入依赖的package包/类
/**
* Trains and returns a {@link CRFTagger} on the specified {@link Sentence}
* s. This method may take hours or even days to complete. When training,
* you will likely need to increase the amount of memory used by the Java
* virtual machine (try adding "-Xms1024m" to the command line).
*
* @param sentences
* The {@link Sentence}s to train the tagger on
* @param order
* The CRF order to use
* @param useFeatureInduction
* Whether or not to use feature induction
* @param format
* The {@link TagFormat} to use
* @param textDirection
* The {@link TextDirection} to use
* @param lemmatiser
* The {@link Lemmatiser} to use
* @param posTagger
* The part-of-speech {@link dragon.nlp.tool.Tagger} to use
* @param useNumericalNormalization
* Whether to use numeric normalization
* @return A trained CRFTagger; ready to tag unseen sentences or be output
* to disk
*/
public static CRFTagger train(List<Sentence> sentences, int order, boolean useFeatureInduction, TagFormat format, TextDirection textDirection, Lemmatiser lemmatiser,
dragon.nlp.tool.Tagger posTagger, boolean useNumericalNormalization, Tagger preTagger, String regexFilename)
{
if (sentences.size() == 0)
throw new RuntimeException("Number of sentences must be greater than zero");
String2TokenSequencePipe localBasePipe = new String2TokenSequencePipe(lemmatiser, posTagger, useNumericalNormalization, preTagger);
ArrayList<Pipe> pipes = new ArrayList<Pipe>();
pipes.add(localBasePipe);
setupPipes(pipes, regexFilename);
Pipe pipe = new SerialPipes(pipes);
CRF4 forwardCRF = null;
if (textDirection == TextDirection.Intersection)
throw new UnsupportedOperationException("TextDirection.Intersection not yet supported");
if (textDirection.doForward())
forwardCRF = train(sentences, order, useFeatureInduction, format, pipe, false);
CRF4 reverseCRF = null;
if (textDirection.doReverse())
reverseCRF = train(sentences, order, useFeatureInduction, format, pipe, true);
return new CRFTagger(forwardCRF, reverseCRF, localBasePipe, order, useFeatureInduction, format, textDirection);
}
开发者ID:clulab，
项目名称:reach-banner，
代码行数:46，
代码来源:CRFTagger.java
示例5: setLemmatiser
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import dragon.nlp.tool.Lemmatiser; //导入依赖的package包/类
public void setLemmatiser(Lemmatiser lemmatiser)
{
this.lemmatiser = lemmatiser;
}
开发者ID:leebird，
项目名称:legonlp，
代码行数:5，
代码来源:String2TokenSequencePipe.java
示例6: train
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import dragon.nlp.tool.Lemmatiser; //导入依赖的package包/类
/**
* Trains and returns a {@link CRFTagger} on the specified {@link Sentence}s. This method may take hours or even days to complete. When training,
* you will likely need to increase the amount of memory used by the Java virtual machine (try adding "-Xms1024m" to the command line).
*
* @param sentences
* The {@link Sentence}s to train the tagger on
* @param order
* The CRF order to use
* @param useFeatureInduction
* Whether or not to use feature induction
* @param format
* The {@link TagFormat} to use
* @param textDirection
* The {@link TextDirection} to use
* @param lemmatiser
* The {@link Lemmatiser} to use
* @param posTagger
* The part-of-speech {@link dragon.nlp.tool.Tagger} to use
* @param useNumericalNormalization
* Whether to use numeric normalization
* @return A trained CRFTagger; ready to tag unseen sentences or be output to disk
*/
public static CRFTagger train(List<Sentence> sentences, int order, boolean useFeatureInduction, TagFormat format, TextDirection textDirection,
Lemmatiser lemmatiser, dragon.nlp.tool.Tagger posTagger, boolean useNumericalNormalization)
{
if (sentences.size() == 0)
throw new RuntimeException("Number of sentences must be greater than zero");
String2TokenSequencePipe localBasePipe = new String2TokenSequencePipe(lemmatiser, posTagger, useNumericalNormalization);
ArrayList<Pipe> pipes = new ArrayList<Pipe>();
pipes.add(localBasePipe);
setupPipes(pipes);
Pipe pipe = new SerialPipes(pipes);
CRF4 forwardCRF = null;
if (textDirection == TextDirection.Intersection)
throw new UnsupportedOperationException("TextDirection.Intersection not yet supported");
if (textDirection.doForward())
forwardCRF = train(sentences, order, useFeatureInduction, format, pipe, false);
CRF4 reverseCRF = null;
if (textDirection.doReverse())
reverseCRF = train(sentences, order, useFeatureInduction, format, pipe, true);
return new CRFTagger(forwardCRF, reverseCRF, localBasePipe, order, useFeatureInduction, format, textDirection);
}
开发者ID:leebird，
项目名称:legonlp，
代码行数:43，
代码来源:CRFTagger.java
示例7: train
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import dragon.nlp.tool.Lemmatiser; //导入依赖的package包/类
/**
* Trains and returns a {@link CRFTagger} on the specified {@link Sentence}s. This method may take hours or even days to complete. When training,
* you will likely need to increase the amount of memory used by the Java virtual machine (try adding "-Xms1024m" to the command line).
*
* @param sentences
* The {@link Sentence}s to train the tagger on
* @param order
* The crf order to use
* @param useFeatureInduction
* Whether or not to use feature induction
* @param format
* The {@link TagFormat} to use
* @param textDirection
* The {@link TextDirection} to use
* @param lemmatiser
* The {@link Lemmatiser} to use
* @param posTagger
* The part-of-speech {@link dragon.nlp.tool.Tagger} to use
* @param useNumericalNormalization
* Whether to use numeric normalization
* @return A trained CRFTagger; ready to tag unseen sentences or be output to disk
*/
public static CRFTagger train(List<Sentence> sentences, int order, boolean useFeatureInduction, TagFormat format, TextDirection textDirection,
Lemmatiser lemmatiser, dragon.nlp.tool.Tagger posTagger, boolean useNumericalNormalization)
{
if (sentences.size() == 0)
throw new RuntimeException("Number of sentences must be greater than zero");
String2TokenSequencePipe localBasePipe = new String2TokenSequencePipe(lemmatiser, posTagger, useNumericalNormalization);
ArrayList<Pipe> pipes = new ArrayList<Pipe>();
pipes.add(localBasePipe);
setupPipes(pipes);
Pipe pipe = new SerialPipes(pipes);
CRF4 forwardCRF = null;
if (textDirection == TextDirection.Intersection)
throw new UnsupportedOperationException("TextDirection.Intersection not yet supported");
if (textDirection.doForward())
forwardCRF = train(sentences, order, useFeatureInduction, format, pipe, false);
CRF4 reverseCRF = null;
if (textDirection.doReverse())
reverseCRF = train(sentences, order, useFeatureInduction, format, pipe, true);
return new CRFTagger(forwardCRF, reverseCRF, localBasePipe, order, useFeatureInduction, format, textDirection);
}
开发者ID:karahindiba，
项目名称:WikiInfoboxExtractor，
代码行数:43，
代码来源:Banner.java
示例8: load
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import dragon.nlp.tool.Lemmatiser; //导入依赖的package包/类
/**
* Loads a {@link CRFTagger} from the specified file. As the lemmatiser and
* part-of-speech tagger both require data, these cannot be written to disk
* and must be passed in new. This version of the method assumes no
* preTagger; it is primarily intended for backwards compatibility.
*
* @param f
* The file to load the CRFTagger from, as written by the {@link}
* write() method.
* @param lemmatiser
* The {@link Lemmatiser} to use
* @param posTagger
* The part-of-speech {@link dragon.nlp.tool.Tagger} to use
* @throws IOException
* @return A new instance of the CRFTagger contained in the specified file
*/
public static CRFTagger load(File f, Lemmatiser lemmatiser, dragon.nlp.tool.Tagger posTagger) throws IOException
{
return load(f, lemmatiser, posTagger, null);
}
开发者ID:clulab，
项目名称:reach-banner，
代码行数:21，
代码来源:CRFTagger.java
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