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
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Sentence Simplification | PWKP (test) | LD (System -> Simple)14.29 | 16 | |
| Sentence Splitting | Wikipedia BOTH-AB (sentences split by both systems) | Average Score4.75 | 10 | |
| Text Simplification | Wikipedia | Simplicity2.83 | 6 | |
| Sentence Splitting | Wikipedia (ONLY-A sentences split only by UNSUP) | Average Score2.42 | 5 | |
| Sentence Splitting | Wikipedia ALL-B (sentences split) | -- | 5 | |
| Sentence Splitting | Wikipedia ONLY-B sentences split | -- | 5 | |
| Sentence Splitting | Wikipedia ALL-A (sentences split by system A) | Average Score2.37 | 1 |
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