UW-CSE at SemEval-2016 Task 10: Detecting Multiword Expressions and Supersenses using Double-Chained Conditional Random Fields
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چکیده
We describe our entry to SemEval 2016 Task 10: Detecting Minimal Semantic Units and their Meanings. Our approach uses a discriminative first-order sequence model similar to Schneider and Smith (2015). The chief novelty in our approach is a factorization of the labels into multiword expression and supersense labels, and restricting first-order dependencies within these two parts. Our submitted models achieved first place in the closed competition (CRF) and second place in the open competition (2-CRF).
منابع مشابه
UW-CSE: Detecting Multiword Expressions and Supersenses using Double-Chained Conditional Random Fields
We describe our entry to SemEval 2016 Task 10: Detecting Minimal Semantic Units and their Meanings. Our approach uses a discriminative first-order sequence model similar to Schneider and Smith (2015). The chief novelty in our approach is a factorization of the labels into multiword expression and supersense labels, and restricting first-order dependencies within these two parts. Our submitted m...
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This paper presents our approach towards the SemEval-2016 Task 10 – Detecting Minimal Semantic Units and their Meanings. Systems are expected to provide a representation of lexical semantics by (1) segmenting tokens into words and multiword units and (2) providing a supersense tag for segments that function as nouns or verbs. Our pipeline rule-based system uses no external resources and was imp...
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تاریخ انتشار 2016