本文整理匯總了Java中edu.stanford.nlp.ling.CoreLabel.tag方法的典型用法代碼示例。如果您正苦於以下問題：Java CoreLabel.tag方法的具體用法？Java CoreLabel.tag怎麽用？Java CoreLabel.tag使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類edu.stanford.nlp.ling.CoreLabel的用法示例。
在下文中一共展示了CoreLabel.tag方法的4個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Java代碼示例。
示例1: tokenize
import edu.stanford.nlp.ling.CoreLabel; //導入方法依賴的package包/類
public LinkedList<String> tokenize(String text) {
LinkedList<String> res = new LinkedList<>();
if (text != null) {
Annotation qaTokens = new Annotation(text);
pipelineTokens.annotate(qaTokens);
List<CoreMap> qssTokens = qaTokens.get(CoreAnnotations.SentencesAnnotation.class);
for (CoreMap sentenceTokens : qssTokens) {
ArrayList<CoreLabel> tokens = (ArrayList<CoreLabel>) sentenceTokens.get(CoreAnnotations.TokensAnnotation.class);
for (CoreLabel t : tokens) {
String lemma = t.lemma();
String pos = t.tag();
if (!stopwords.contains(lemma)) {
String rep = representativeProvider.getRepresentative(lemma, pos);
if (!stopwords.contains(rep)) {
res.add(rep);
}
}
}
}
}
return res;
}
示例2: preprocess
import edu.stanford.nlp.ling.CoreLabel; //導入方法依賴的package包/類
public Concept preprocess(Concept c) {
if (this.tagger == null)
this.tagger = new MaxentTagger("ext_models/pos_tagger/english-left3words-distsim.tagger");
if (this.ner == null)
this.ner = CRFClassifier.getClassifierNoExceptions("ext_models/ner/english.all.3class.distsim.crf.ser.gz");
List<CoreLabel> words = tokFactory.getTokenizer(new StringReader(c.name)).tokenize();
tagger.tagCoreLabels(words);
words = ner.classifySentence(words);
words = this.addLemmas(words);
List<PToken> tokens = new ArrayList<PToken>();
for (CoreLabel word : words) {
PToken t = new PToken(word.originalText());
t.pos = word.tag();
t.neTag = word.get(CoreAnnotations.AnswerAnnotation.class);
t.lemma = word.get(LemmaAnnotation.class);
tokens.add(t);
}
c.tokenList = tokens;
return c;
}
示例3: simpleTokenization
import edu.stanford.nlp.ling.CoreLabel; //導入方法依賴的package包/類
public LinkedList<String> simpleTokenization(String text) {
LinkedList<String> res = new LinkedList<>();
if (text != null) {
Annotation qaTokens = new Annotation(text);
pipelineTokens.annotate(qaTokens);
List<CoreMap> qssTokens = qaTokens.get(CoreAnnotations.SentencesAnnotation.class);
for (CoreMap sentenceTokens : qssTokens) {
ArrayList<CoreLabel> tokens = (ArrayList<CoreLabel>) sentenceTokens.get(CoreAnnotations.TokensAnnotation.class);
for (CoreLabel t : tokens) {
String lemma = t.lemma();
String pos = t.tag();
if ((pos.startsWith("N") || pos.startsWith("V")) && !stopwords.contains(lemma)) {
res.add(lemma);
}
}
}
}
return res;
}
示例4: tokenizeBySentence
import edu.stanford.nlp.ling.CoreLabel; //導入方法依賴的package包/類
public LinkedList<LinkedList<String>> tokenizeBySentence(String text, LinkedList<int[]> boundaries) {
LinkedList<LinkedList<String>> res = new LinkedList<>();
if (text != null) {
Annotation qaTokens = new Annotation(text);
pipelineTokens.annotate(qaTokens);
List<CoreMap> qssTokens = qaTokens.get(CoreAnnotations.SentencesAnnotation.class);
for (CoreMap sentenceTokens : qssTokens) {
ArrayList<CoreLabel> tokens = (ArrayList<CoreLabel>) sentenceTokens.get(CoreAnnotations.TokensAnnotation.class);
LinkedList<String> sentence=new LinkedList<>();
boolean first=true;
int[] bounds=new int[2];
CoreLabel last=null;
for (CoreLabel t : tokens) {
if (first) {
bounds[0]=t.beginPosition();
first=false;
}
last=t;
String lemma = t.lemma();
String pos = t.tag();
if (!stopwords.contains(lemma)) {
String rep = representativeProvider.getRepresentative(lemma, pos);
if (!stopwords.contains(rep)) {
sentence.add(rep);
}
}
}
bounds[1]=last.endPosition();
if (sentence.size()>0) {
res.add(sentence);
boundaries.add(bounds);
}
}
}
return res;
}