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- W4300908084 abstract "We propose a neural-network based model for coordination boundary prediction. The network is designed to incorporate two signals: the similarity between conjuncts and the observation that replacing the whole coordination phrase with a conjunct tends to produce a coherent sentences. The modeling makes use of several LSTM networks. The model is trained solely on conjunction annotations in a Treebank, without using external resources. We show improvements on predicting coordination boundaries on the PTB compared to two state-of-the-art parsers; as well as improvement over previous coordination boundary prediction systems on the Genia corpus." @default.
- W4300908084 created "2022-10-04" @default.
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- W4300908084 date "2016-10-13" @default.
- W4300908084 modified "2023-09-26" @default.
- W4300908084 title "A Neural Network for Coordination Boundary Prediction" @default.
- W4300908084 doi "https://doi.org/10.48550/arxiv.1610.03946" @default.
- W4300908084 hasPublicationYear "2016" @default.
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