斯坦福CoreNLP服务器的JSON响应缺少RelationExtractor注释

Question

我正在处理一个简单的句子来测试斯坦福大学的RelationExtractor

微软总部设在纽约。

(不是)

当我用Java注释这个句子时，通过直接使用CoreNLP jar文件，我得到了想要的结果-- CoreNLP在微软和纽约之间找到了一个OrgBased_In关系。

for (CoreMap sentence : sentences) {
    relationType = sentence.get(MachineReadingAnnotations.RelationMentionsAnnotation.class).get(0).type // => OrgBased_In
}

但是，将相同的句子发送到CoreNLP服务器中如下：

curl --data 'Microsoft is based in New York.' 'http://localhost:9000/?properties={%22annotators%22%3A%22tokenize%2Cssplit%2Cpos%2Clemma%2Cner%2Cparse%2Cdepparse%2Crelation%22%2C%22outputFormat%22%3A%22json%22}' -o -

其结果是，json的答复中没有任何关于关系的数据：

{'sentences': [{'basicDependencies': [{'dep': 'ROOT',
                                   'dependent': 3,
                                   'dependentGloss': 'based',
                                   'governor': 0,
                                   'governorGloss': 'ROOT'},
                                  {'dep': 'nsubjpass',
                                   'dependent': 1,
                                   'dependentGloss': 'Microsoft',
                                   'governor': 3,
                                   'governorGloss': 'based'},
                                  {'dep': 'auxpass',
                                   'dependent': 2,
                                   'dependentGloss': 'is',
                                   'governor': 3,
                                   'governorGloss': 'based'},
                                  {'dep': 'case',
                                   'dependent': 4,
                                   'dependentGloss': 'in',
                                   'governor': 6,
                                   'governorGloss': 'York'},
                                  {'dep': 'compound',
                                   'dependent': 5,
                                   'dependentGloss': 'New',
                                   'governor': 6,
                                   'governorGloss': 'York'},
                                  {'dep': 'nmod',
                                   'dependent': 6,
                                   'dependentGloss': 'York',
                                   'governor': 3,
                                   'governorGloss': 'based'},
                                  {'dep': 'punct',
                                   'dependent': 7,
                                   'dependentGloss': '.',
                                   'governor': 3,
                                   'governorGloss': 'based'}],
            'enhancedDependencies': [{'dep': 'ROOT',
                                      'dependent': 3,
                                      'dependentGloss': 'based',
                                      'governor': 0,
                                      'governorGloss': 'ROOT'},
                                     {'dep': 'nsubjpass',
                                      'dependent': 1,
                                      'dependentGloss': 'Microsoft',
                                      'governor': 3,
                                      'governorGloss': 'based'},
                                     {'dep': 'auxpass',
                                      'dependent': 2,
                                      'dependentGloss': 'is',
                                      'governor': 3,
                                      'governorGloss': 'based'},
                                     {'dep': 'case',
                                      'dependent': 4,
                                      'dependentGloss': 'in',
                                      'governor': 6,
                                      'governorGloss': 'York'},
                                     {'dep': 'compound',
                                      'dependent': 5,
                                      'dependentGloss': 'New',
                                      'governor': 6,
                                      'governorGloss': 'York'},
                                     {'dep': 'nmod:in',
                                      'dependent': 6,
                                      'dependentGloss': 'York',
                                      'governor': 3,
                                      'governorGloss': 'based'},
                                     {'dep': 'punct',
                                      'dependent': 7,
                                      'dependentGloss': '.',
                                      'governor': 3,
                                      'governorGloss': 'based'}],
            'enhancedPlusPlusDependencies': [{'dep': 'ROOT',
                                              'dependent': 3,
                                              'dependentGloss': 'based',
                                              'governor': 0,
                                              'governorGloss': 'ROOT'},
                                             {'dep': 'nsubjpass',
                                              'dependent': 1,
                                              'dependentGloss': 'Microsoft',
                                              'governor': 3,
                                              'governorGloss': 'based'},
                                             {'dep': 'auxpass',
                                              'dependent': 2,
                                              'dependentGloss': 'is',
                                              'governor': 3,
                                              'governorGloss': 'based'},
                                             {'dep': 'case',
                                              'dependent': 4,
                                              'dependentGloss': 'in',
                                              'governor': 6,
                                              'governorGloss': 'York'},
                                             {'dep': 'compound',
                                              'dependent': 5,
                                              'dependentGloss': 'New',
                                              'governor': 6,
                                              'governorGloss': 'York'},
                                             {'dep': 'nmod:in',
                                              'dependent': 6,
                                              'dependentGloss': 'York',
                                              'governor': 3,
                                              'governorGloss': 'based'},
                                             {'dep': 'punct',
                                              'dependent': 7,
                                              'dependentGloss': '.',
                                              'governor': 3,
                                              'governorGloss': 'based'}],
            'index': 0,
            'parse': '(ROOT\n'
                     '  (S\n'
                     '    (NP (NNP Microsoft))\n'
                     '    (VP (VBZ is)\n'
                     '      (VP (VBN based)\n'
                     '        (PP (IN in)\n'
                     '          (NP (NNP New) (NNP York)))))\n'
                     '    (. .)))',
            'tokens': [{'after': ' ',
                        'before': '',
                        'characterOffsetBegin': 0,
                        'characterOffsetEnd': 9,
                        'index': 1,
                        'lemma': 'Microsoft',
                        'ner': 'ORGANIZATION',
                        'originalText': 'Microsoft',
                        'pos': 'NNP',
                        'word': 'Microsoft'},
                       {'after': ' ',
                        'before': ' ',
                        'characterOffsetBegin': 10,
                        'characterOffsetEnd': 12,
                        'index': 2,
                        'lemma': 'be',
                        'ner': 'O',
                        'originalText': 'is',
                        'pos': 'VBZ',
                        'word': 'is'},
                       {'after': ' ',
                        'before': ' ',
                        'characterOffsetBegin': 13,
                        'characterOffsetEnd': 18,
                        'index': 3,
                        'lemma': 'base',
                        'ner': 'O',
                        'originalText': 'based',
                        'pos': 'VBN',
                        'word': 'based'},
                       {'after': ' ',
                        'before': ' ',
                        'characterOffsetBegin': 19,
                        'characterOffsetEnd': 21,
                        'index': 4,
                        'lemma': 'in',
                        'ner': 'O',
                        'originalText': 'in',
                        'pos': 'IN',
                        'word': 'in'},
                       {'after': ' ',
                        'before': ' ',
                        'characterOffsetBegin': 22,
                        'characterOffsetEnd': 25,
                        'index': 5,
                        'lemma': 'New',
                        'ner': 'LOCATION',
                        'originalText': 'New',
                        'pos': 'NNP',
                        'word': 'New'},
                       {'after': '',
                        'before': ' ',
                        'characterOffsetBegin': 26,
                        'characterOffsetEnd': 30,
                        'index': 6,
                        'lemma': 'York',
                        'ner': 'LOCATION',
                        'originalText': 'York',
                        'pos': 'NNP',
                        'word': 'York'},
                       {'after': '',
                        'before': '',
                        'characterOffsetBegin': 30,
                        'characterOffsetEnd': 31,
                        'index': 7,
                        'lemma': '.',
                        'ner': 'O',
                        'originalText': '.',
                        'pos': '.',
                        'word': '.'}]}]}

我可以在CoreNLP服务器终端上看到，关系提取模型已经加载。

[pool-1-thread-1] INFO edu.stanford.nlp.pipeline.RelationExtractorAnnotator - Loading relation model from edu/stanford/nlp/models/supervised_relation_extractor/roth_relation_model_pipelineNER.ser

我在这里错过了什么？

谢谢!

Answer 1

我认为最终没有人将输出添加到注释器的JSON中，我们最终可以这样做。

目前，我们主要支持的关系提取是新的kbp注释器。这就从TAC的挑战中提取出关系。

您可以在这里找到关系描述：V1.0.pdf

下面是我运行的一个示例命令：

java -Xmx8g edu.stanford.nlp.pipeline.StanfordCoreNLP -annotators tokenize,ssplit,pos,lemma,ner,parse,mention,entitymentions,coref,kbp -file microsoft-example.txt -outputFormat json

如果您查看JSON，您将看到正确的关系已被提取。