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arXiv · 1902.00489

Human acceptability judgements for extractive sentence compression

Abram Handler·Brian Dillon·Brendan O'Connor
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Abstract

Recent approaches to English-language sentence compression rely on parallel corpora consisting of sentence-compression pairs. However, a sentence may be shortened in many different ways, which each might be suited to the needs of a particular application. Therefore, in this work, we collect and model crowdsourced judgements of the acceptability of many possible sentence shortenings. We then show how a model of such judgements can be used to support a flexible approach to the compression task. We release our model and dataset for future work.

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Abram Handler, Brian Dillon, Brendan O'Connor. 2019-02-01. Human acceptability judgements for extractive sentence compression. https://arxiv.org/abs/1902.00489

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