2017
ACL
ACL 2017
English Multiword Expression-aware Dependency Parsing Including Named Entities
Abstract
AbstractBecause syntactic structures and spans of multiword expressions (MWEs) are independently annotated in many English syntactic corpora, they are generally inconsistent with respect to one another, which is harmful to the implementation of an aggregate system. In this work, we construct a corpus that ensures consistency between dependency structures and MWEs, including named entities. Further, we explore models that predict both MWE-spans and an MWE-aware dependency structure. Experimental results show that our joint model using additional MWE-span features achieves an MWE recognition improvement of 1.35 points over a pipeline model.
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Trend Setter
— Named Entity Recognition
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Keyword Pioneer
— joint model
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio
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Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
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Hot Topic Early Bird
— joint learning
Authors
Topics
Natural Language Processing > Understanding > Named Entity Recognition
Natural Language Processing > Understanding > Parsing
Natural Language Processing > Understanding > Syntax
Machine Learning > Learning Types > Multi-Task Learning
Natural Language Processing > Applications > Named Entity Recognition