Papers › Unsupervised Sentence Simplification Using Deep Semantics
Unsupervised Sentence Simplification Using Deep Semantics
Shashi Narayan, Claire Gardent
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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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Text Simplification | PWKP / WikiSmall | UNSUP | BLEU | 38.47 | #2 of 11 | Archive leaderboard | report |
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