Unsupervised Sentence Simplification Using Deep Semantics

Shashi Narayan 1 Claire Gardent 2
2 SYNALP - Natural Language Processing : representations, inference and semantics
LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : We present a novel approach to sentence simplification which departs from previous work in two main ways. First, it requires neither hand written rules nor a training corpus of aligned standard and simplified sentences. Second, sentence splitting operates on deep semantic structure. We show (i) that the unsupervised framework we propose is competitive with four state-of-the-art supervised systems and (ii) that our semantic based approach allows for a principled and effective handling of sentence splitting.
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Communication dans un congrès
The 9th International Natural Language Generation conference, Sep 2016, Edinburgh, United Kingdom. pp.111 - 120, 2016, 〈10.18653/v1/W16-6620〉
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Shashi Narayan, Claire Gardent. Unsupervised Sentence Simplification Using Deep Semantics. The 9th International Natural Language Generation conference, Sep 2016, Edinburgh, United Kingdom. pp.111 - 120, 2016, 〈10.18653/v1/W16-6620〉. 〈hal-01623829〉

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