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Natural chunk-and-pass language processing: Just another joint source-channel coding model?
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Improving Coreference Resolution by Learning Entity-Level Distributed Representations ...
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Abstract:
A long-standing challenge in coreference resolution has been the incorporation of entity-level information - features defined over clusters of mentions instead of mention pairs. We present a neural network based coreference system that produces high-dimensional vector representations for pairs of coreference clusters. Using these representations, our system learns when combining clusters is desirable. We train the system with a learning-to-search algorithm that teaches it which local decisions (cluster merges) will lead to a high-scoring final coreference partition. The system substantially outperforms the current state-of-the-art on the English and Chinese portions of the CoNLL 2012 Shared Task dataset despite using few hand-engineered features. ... : Accepted for publication at the Association for Computational Linguistics (ACL), 2016 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1606.01323
https://arxiv.org/abs/1606.01323
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Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora ...
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Large-scale Analysis of Counseling Conversations: An Application of Natural Language Processing to Mental Health ...
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Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora
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Large-scale Analysis of Counseling Conversations: An Application of Natural Language Processing to Mental Health
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Social biases determine spatiotemporal sparseness of ciliate mating heuristics
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