We study the influence of context on sentence acceptability. First we compare the acceptability ratings of sentences judged in isolation, with a relevant context, and with an irrelevant context. Our results show that context induces a cognitive load for humans, which compresses the distribution of ratings. Moreover, in relevant contexts we observe a discourse coherence effect which uniformly raises acceptability. Next, we test unidirectional and bidirectional language models in their ability to predict acceptability ratings. The bidirectional models show very promising results, with the best model achieving a new state-of-the-art for unsupervised acceptability prediction. The two sets of experiments provide insights into the cognitive aspects of sentence processing and central issues in the computational modelling of text and discourse.

研究上下文对句子可接受性的影响，结论是上下文会使人们承受认知负担，从而压缩了评分分布，而在相关上下文中观察到的话语连贯性效应可以一致地提高接受度；此外，测试了单向和双向语言模型在预测可接受性评级方面的能力，表明双向模型取得了极具前景的结果，最佳模型实现了无监督接受性预测的最新水平。

无色的绿色观念能以多大的愤怒睡觉? 上下文中的句子可接受性