我正在使用斯坦福 CoreNLP。我需要检测并识别输入文本中每个 CorefChain 的“共指集”和“代表性提及”:
For example: Input: Obama was elected to the Illinois state senate in 1996 and served there for eight years. 2004年,他以创纪录的多数席位从伊利诺伊州选出,并于2007年2月宣布了他的总统候选人资格。
输出:使用“Pretty Print”我可以得到以下输出:
**Coreference set:
(2,4,[4,5]) -> (1,1,[1,2]), that is: "he" -> "Obama"
(2,24,[24,25]) -> (1,1,[1,2]), that is: "his" -> "Obama"
(3,22,[22,23]) -> (1,1,[1,2]), that is: "Obama" -> "Obama"**
但是,我需要以编程方式识别和检测上面的输出,称为“共指集”。(我的意思是我需要识别所有对,例如:“he”->“Obama”)
注意:我的基本代码如下(来自http://stanfordnlp.github.io/CoreNLP/coref.html):
import edu.stanford.nlp.hcoref.CorefCoreAnnotations;
import edu.stanford.nlp.hcoref.data.CorefChain;
import edu.stanford.nlp.hcoref.data.Mention;
import edu.stanford.nlp.ling.CoreAnnotations;
import edu.stanford.nlp.pipeline.Annotation;
import edu.stanford.nlp.pipeline.StanfordCoreNLP;
import edu.stanford.nlp.util.CoreMap;
import java.util.Properties;
public class CorefExample {
public static void main(String[] args) throws Exception {
Annotation document = new Annotation("Obama was elected to the Illinois state senate in 1996 and served there for eight years. In 2004, he was elected by a record majority to the U.S. Senate from Illinois and, in February 2007, announced his candidacy for President.");
Properties props = new Properties();
props.setProperty("annotators", "tokenize,ssplit,pos,lemma,ner,parse,mention,coref");
StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
pipeline.annotate(document);
System.out.println("---");
System.out.println("coref chains");
for (CorefChain cc : document.get(CorefCoreAnnotations.CorefChainAnnotation.class).values()) {
System.out.println("\t"+cc);
}
for (CoreMap sentence : document.get(CoreAnnotations.SentencesAnnotation.class)) {
System.out.println("---");
System.out.println("mentions");
for (Mention m : sentence.get(CorefCoreAnnotations.CorefMentionsAnnotation.class)) {
System.out.println("\t"+m);
}
}
}
}
///// Any Idea? THANK YOU in ADVANCE