Fine-Grained Evaluation for Entity Linking

EMNLP/IJCNLP (1)(2019)

引用 14|浏览373
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摘要
The Entity Linking (EL) task identifies entity mentions in a text corpus and associates them with an unambiguous identifier in a Knowledge Base. While much work has been done on the topic, we first present the results of a survey that reveal a lack of consensus in the community regarding what forms of mentions in a text and what forms of links the EL task should consider. We argue that no one definition of the Entity Linking task fits all, and rather propose a fine-grained cate-gorization of different types of entity mentions and links. We then re-annotate three EL benchmark datasets-ACE2004, KORE50, and VoxEL-with respect to these categories. We propose a fuzzy recall metric to address the lack of consensus and conclude with fine-grained evaluation results comparing a selection of online EL systems.
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关键词
Entity linking,Text corpus,Identifier,Knowledge base,Natural language processing,Recall,Fuzzy logic,Computer science,Artificial intelligence
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