抽取式句子压缩的人类可接受性判断
Human acceptability judgements for extractive sentence compression
摘要：
最近的英语句子压缩方法依赖于由重复压缩对组成的平行语料库。然而，一个句子可以用许多不同的方式缩短，每一种方式都可能适合于特定应用的需要。因此，在这项工作中，我们收集和模型众包的判断，许多可能的句子缩短的可接受性。然后，我们将展示如何使用这种判断的模型来支持压缩任务的灵活方法。我们发布了我们的模型和数据集，以供未来工作使用。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
