通過閱讀文檔和使用 API，看起來 CoreNLP 會告訴我每個標(biāo)記的 NER 標(biāo)簽，但它不會幫助我從句子中提取全名。例如：Input:?John?Wayne?and?Mary?have?coffee
CoreNLP?Output:?(John,PERSON)?(Wayne,PERSON)?(and,O)?(Mary,PERSON)?(have,O)?(coffee,O)
Desired?Result:?list?of?PERSON?==>?[John?Wayne,?Mary]除非我錯過了一些標(biāo)志，否則我相信要做到這一點，我將需要解析標(biāo)記并將標(biāo)記為 PERSON 的連續(xù)標(biāo)記粘合在一起。有人可以確認(rèn)這確實是我需要做的嗎？我主要想知道 CoreNLP 中是否有一些標(biāo)志或?qū)嵱贸绦蚩梢詾槲易鲞@樣的事情。如果有人有實用程序（最好是 Java，因為我使用的是 Java API）可以執(zhí)行此操作并希望分享，則可加分 :)謝謝！
2 回答
白板的微信
TA貢獻(xiàn)1883條經(jīng)驗 獲得超3個贊
您可能正在尋找實體提及而不是 NER 標(biāo)簽。例如使用簡單 API：
new Sentence("Jimi Hendrix was the greatest").nerTags()
[PERSON, PERSON, O, O, O]
new Sentence("Jimi Hendrix was the greatest").mentions()
[Jimi Hendrix]
StanfordCoreNLP上面的鏈接有一個使用舊管道的傳統(tǒng)非簡單 API 的示例
qq_笑_17
TA貢獻(xiàn)1818條經(jīng)驗 獲得超7個贊
這是完整的 Java API 示例，其中有一個關(guān)于實體提及的部分：
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();
? }
}
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