Lexicosyntactic Inference in Neural Models
Aaron Steven White, Rachel Rudinger, Kyle Rawlins, Benjamin Van Durme
August 2018 

We investigate neural models' ability to capture lexicosyntactic inferences: inferences triggered by the interaction of lexical and syntactic information. We take the task of event factuality prediction as a case study and build a factuality judgment dataset for all English clause-embedding verbs in various syntactic contexts. We use this dataset, which we make publicly available, to probe the behavior of current state-of-the-art neural systems, showing that these systems make certain systematic errors that are clearly visible through the lens of factuality prediction.

Format:	[ pdf ]
Reference:	lingbuzz/004162 (please use that when you cite this article)
Published in:	Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
keywords:	factive, veridical, implicative, infinitival, neural, rnn, lstm, semantics
Downloaded:	338 times

 

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