使用StanfordCoreNLP管道而不是AnnotationPipeline提取日期

Question

当我使用StanfordCoreNLP的SUTime功能并使用其文档中给出的代码（涉及使用AnnotationPipeline创建管道对象）时，便能够从字符串中成功提取TIME。

使用的代码是：

但是我的项目需要StanfordCoreNLP管道，所以当我使用相同的管道提取TIME时，它给了我NULLPointerException。 我的代码如下：

我遇到的错误如下：

我还在此链接中尝试了@StanfordNLPHelp建议的解决方案： Dates when using StanfordCoreNLP pipeline

代码如下：

但是错误仍然存​​在：

Answer 1

标准ner注释器将运行SUTime。请查看此链接以获取Java API信息：

https://stanfordnlp.github.io/CoreNLP/api.html

基本示例：

import edu.stanford.nlp.coref.data.CorefChain;
import edu.stanford.nlp.ling.*;
import edu.stanford.nlp.ie.util.*;
import edu.stanford.nlp.pipeline.*;
import edu.stanford.nlp.semgraph.*;
import edu.stanford.nlp.trees.*;
import java.util.*;


public class BasicPipelineExample {

  public static String text = "Joe Smith was born in California. " +
      "In 2017, he went to Paris, France in the summer. " +
      "His flight left at 3:00pm on July 10th, 2017. " +
      "After eating some escargot for the first time, Joe said, \"That was delicious!\" " +
      "He sent a postcard to his sister Jane Smith. " +
      "After hearing about Joe's trip, Jane decided she might go to France one day.";

  public static void main(String[] args) {
    // set up pipeline properties
    Properties props = new Properties();
    // set the list of annotators to run
    props.setProperty("annotators", "tokenize,ssplit,pos,lemma,ner,parse,depparse,coref,kbp,quote");
    // set a property for an annotator, in this case the coref annotator is being set to use the neural algorithm
    props.setProperty("coref.algorithm", "neural");
    // build pipeline
    StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
    // create a document object
    CoreDocument document = new CoreDocument(text);
    // annnotate the document
    pipeline.annotate(document);
    // examples

    // 10th token of the document
    CoreLabel token = document.tokens().get(10);
    System.out.println("Example: token");
    System.out.println(token);
    System.out.println();

    // text of the first sentence
    String sentenceText = document.sentences().get(0).text();
    System.out.println("Example: sentence");
    System.out.println(sentenceText);
    System.out.println();

    // second sentence
    CoreSentence sentence = document.sentences().get(1);

    // list of the part-of-speech tags for the second sentence
    List<String> posTags = sentence.posTags();
    System.out.println("Example: pos tags");
    System.out.println(posTags);
    System.out.println();

    // list of the ner tags for the second sentence
    List<String> nerTags = sentence.nerTags();
    System.out.println("Example: ner tags");
    System.out.println(nerTags);
    System.out.println();

    // constituency parse for the second sentence
    Tree constituencyParse = sentence.constituencyParse();
    System.out.println("Example: constituency parse");
    System.out.println(constituencyParse);
    System.out.println();

    // dependency parse for the second sentence
    SemanticGraph dependencyParse = sentence.dependencyParse();
    System.out.println("Example: dependency parse");
    System.out.println(dependencyParse);
    System.out.println();

    // kbp relations found in fifth sentence
    List<RelationTriple> relations =
        document.sentences().get(4).relations();
    System.out.println("Example: relation");
    System.out.println(relations.get(0));
    System.out.println();

    // entity mentions in the second sentence
    List<CoreEntityMention> entityMentions = sentence.entityMentions();
    System.out.println("Example: entity mentions");
    System.out.println(entityMentions);
    System.out.println();

    // coreference between entity mentions
    CoreEntityMention originalEntityMention = document.sentences().get(3).entityMentions().get(1);
    System.out.println("Example: original entity mention");
    System.out.println(originalEntityMention);
    System.out.println("Example: canonical entity mention");
    System.out.println(originalEntityMention.canonicalEntityMention().get());
    System.out.println();

    // get document wide coref info
    Map<Integer, CorefChain> corefChains = document.corefChains();
    System.out.println("Example: coref chains for document");
    System.out.println(corefChains);
    System.out.println();

    // get quotes in document
    List<CoreQuote> quotes = document.quotes();
    CoreQuote quote = quotes.get(0);
    System.out.println("Example: quote");
    System.out.println(quote);
    System.out.println();

    // original speaker of quote
    // note that quote.speaker() returns an Optional
    System.out.println("Example: original speaker of quote");
    System.out.println(quote.speaker().get());
    System.out.println();

    // canonical speaker of quote
    System.out.println("Example: canonical speaker of quote");
    System.out.println(quote.canonicalSpeaker().get());
    System.out.println();

  }

}

如果只需要DATE，可以在ner之后删除注释符。

Answer 2

使用产生的TIMEX3格式相同：
obj.get（TimeExpression.Annotation.class）.getTemporal（）---> 2018-06-29T17：00
当我将ner tagger与StanfordCoreNLP管道一起使用时，存储在NormalizedNamedEntityTagAnnotation.class中。详细信息可以在documentation of Stanford Temporal Tagger

中找到

以下代码在提取日期时效果很好：