A corpus and model integrating multiword expressions and supersenses

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Abstract

This paper introduces a task of identifying and semantically classifying lexical expressions in running text. We investigate the online reviews genre, adding semantic supersense annotations to a 55,000 word English corpus that was previously annotated for multiword expressions. The noun and verb supersenses apply to full lexical expressions, whether single- or multiword. We then present a sequence tagging model that jointly infers lexical expressions and their supersenses. Results show that even with our relatively small training corpus in a noisy domain, the joint task can be performed to attain 70% class labeling F1.

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APA

Schneider, N., & Smith, N. A. (2015). A corpus and model integrating multiword expressions and supersenses. In NAACL HLT 2015 - 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference (pp. 1537–1547). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/n15-1177

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