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Unsupervised Sentence Simplification Using Deep Semantics

About

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.

Shashi Narayan, Claire Gardent• 2015

Related benchmarks

TaskDatasetResultRank
Sentence SimplificationPWKP (test)
LD (System -> Simple)14.29
16
Sentence SplittingWikipedia BOTH-AB (sentences split by both systems)
Average Score4.75
10
Text SimplificationWikipedia
Simplicity2.83
6
Sentence SplittingWikipedia (ONLY-A sentences split only by UNSUP)
Average Score2.42
5
Sentence SplittingWikipedia ALL-B (sentences split)--
5
Sentence SplittingWikipedia ONLY-B sentences split--
5
Sentence SplittingWikipedia ALL-A (sentences split by system A)
Average Score2.37
1
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