Neural Discourse Segmentation
Keyword(s):
Identifying discourse structures and coherence relations in a piece of text is a fundamental task in natural language processing. The first step of this process is segmenting sentences into clause-like units called elementary discourse units (EDUs). Traditional solutions to discourse segmentation heavily rely on carefully designed features. In this demonstration, we present SegBot, a system to split a given piece of text into sequence of EDUs by using an end-to-end neural segmentation model. Our model does not require hand-crafted features or external knowledge except word embeddings, yet it outperforms state-of-the-art solutions to discourse segmentation.
2017 ◽
Vol 24
(4)
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pp. 813-821
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2020 ◽
Vol 34
(05)
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pp. 9426-9433
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Keyword(s):
2015 ◽
Vol 21
(5)
◽
pp. 699-724
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2012 ◽
Vol 45
(5)
◽
pp. 825-826
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Keyword(s):