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No noun phrase left behind: Detecting and typing unlinkable entities
Abstract Entity linking systems link noun-phrase meEntity linking systems link noun-phrase mentions in text to their corresponding Wikipedia articles. However, NLP applications would gain from the ability to detect and type all entities mentioned in text, including the long tail of entities not prominent enough to have their own Wikipedia articles. In this paper we show that once the Wikipedia entities mentioned in a corpus of textual assertions are linked, this can further enable the detection and fine-grained typing of the unlinkable entities. Our proposed method for detecting un-linkable entities achieves 24% greater accuracy than a Named Entity Recognition baseline, and our method for fine-grained typing is able to propagate over 1,000 types from linked Wikipedia entities to unlinkable entities. Detection and typing of unlinkable entities can increase yield for NLP applications such as typed question answering.ications such as typed question answering.
Abstractsub Entity linking systems link noun-phrase meEntity linking systems link noun-phrase mentions in text to their corresponding Wikipedia articles. However, NLP applications would gain from the ability to detect and type all entities mentioned in text, including the long tail of entities not prominent enough to have their own Wikipedia articles. In this paper we show that once the Wikipedia entities mentioned in a corpus of textual assertions are linked, this can further enable the detection and fine-grained typing of the unlinkable entities. Our proposed method for detecting un-linkable entities achieves 24% greater accuracy than a Named Entity Recognition baseline, and our method for fine-grained typing is able to propagate over 1,000 types from linked Wikipedia entities to unlinkable entities. Detection and typing of unlinkable entities can increase yield for NLP applications such as typed question answering.ications such as typed question answering.
Bibtextype inproceedings  +
Has author Lin T. + , Mausam + , Etzioni O. +
Has extra keyword Long tail + , Named entity recognition + , Noun phrase + , Question answering + , Wikipedia + , Wikipedia articles + , Natural language processing systems +
Isbn 9781937284435  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 893–903  +
Published in EMNLP-CoNLL 2012 - 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Proceedings of the Conference +
Title No noun phrase left behind: Detecting and typing unlinkable entities +
Type conference paper  +
Year 2012 +
Creation dateThis property is a special property in this wiki. 8 November 2014 03:48:20  +
Categories Publications without keywords parameter  + , Publications without license parameter  + , Publications without DOI parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 8 November 2014 03:48:20  +
DateThis property is a special property in this wiki. 2012  +
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