Stanford NLP 3.9.0:使用CoreEntityMention是否合并相邻实体的提及? [英] Stanford NLP 3.9.0: Does using CoreEntityMention combine adjacent entity mentions?

问题描述

我正在测试，让实体使用CoreEntityMention提及新的3.9.0方法.我做类似的事情:

I am testing out getting entity mentions the new 3.9.0 way with CoreEntityMention. I do something like:

    CoreDocument document = new CoreDocument(text);
    stanfordPipe = createNerPipeline();
    stanfordPipe.annotate(document);

    for (CoreSentence sentence : document.sentences()) {
        logger.debug("Found sentence {}", sentence);
        if (sentence.entityMentions() == null) continue;
        for (CoreEntityMention cem : sentence.entityMentions()) {
            logger.debug("Found em {}", stringify(cem));            
        }
    }

当我使用sentence.entityMentions()遍历实体提及时，我看到生成的某些实体提及是多令牌实体提及.获取实体提及并纠正我的错误的旧方法是，您必须遍历CoreLabel，因此必须结合自己的多令牌实体提及.

When I iterate through entity mentions using sentence.entityMentions() I see that some of the entity mentions produced are multi-token entity mentions. The old way of getting entity mentions, and correct me if I am wrong, is that you have to iterate over CoreLabel and therefore have to combine the multi-token entity mentions yourself.

那么，在结合具有相同ner标签的相邻标记之前，是否存在一些不存在的新方法?还是我错过了结合多令牌实体提及的旧方法?

So is there some new method that did not exist before to combine adjacent tokens with the same ner label? Or have I missed older ways to combine multi-token entity mentions?

推荐答案

您好！感谢您使用新界面！

Hi thanks for using the new interface!

是的，CoreEntityMention应该代表完整的实体说明.这是添加的一些新语法，有助于简化我们的代码.

Yes, the CoreEntityMention is supposed to represent a full entity mention. This was some new syntax added to help make it easier to work with our code.

传统上，需要诸如句子.get(CoreAnnotations.TokensAnnotation.class)...之类的东西，因此我们尝试添加一些包装器类，以便人们可以使用管道接口，但语法不繁琐

Traditionally there has been a need for things like sentence.get(CoreAnnotations.TokensAnnotation.class)...etc...so we tried to add some wrapper classes so people could use the pipeline interface but not have the cumbersome syntax.

使用这种新近推出的语法，您可以编写:

With this newly debuted syntax, you can write:

sentence.tokens();

关于实体提及，如果句子是乔·史密斯去夏威夷".您会得到两个实体提及:

Regarding entity mentions, if the sentence is "Joe Smith went to Hawaii." you would get two entity mentions:

Joe Smith(2个令牌) 夏威夷(1个令牌)

Joe Smith (2 tokens) Hawaii (1 token)

传统上，ner注释器会使用其命名的实体类型标记句子中的每个标记.然后，单独的entitymentions注释器将构建Mention注释，这些注释是完整实体提及的CoreMap表示形式(例如Joe Smith).

Traditionally the ner annotator would tag every token in the sentence with it's named entity type. Then a separate entitymentions annotator would build Mention annotations which were CoreMap representations of full entity mentions (e.g. Joe Smith).

多年来，我已经看到很多人问:我如何从标记的标记序列转到完整的实体提及?"因此，针对此问题，我们试图使提取句子中提到的完整实体变得容易得多.

I've seen a lot of people over the years ask "How do I go from a tagged sequence of tokens to the full entity mentions?" So in response to this we tried to make it a lot easier to just extract the full entity's referred to in the sentence.

我还应该指出，在大多数情况下，较旧的方法仍然可以使用.我们将在完成3.9.0版本的发布过程中更新文档！

I should also note that for the most part the older ways should still work. Updated documentation is on the way as we work on finalizing the 3.9.0 release!

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