Lexicosyntactic Inference in Neural Models

Aaron Steven White; Rachel Rudinger; Kyle Rawlins; Benjamin Van Durme

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arXiv · 1808.06232

Lexicosyntactic Inference in Neural Models

Aaron Steven White·Rachel Rudinger·Kyle Rawlins·Benjamin Van Durme

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Abstract

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.

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Aaron Steven White, Rachel Rudinger, Kyle Rawlins, Benjamin Van Durme. 2018-08-19. Lexicosyntactic Inference in Neural Models. https://arxiv.org/abs/1808.06232

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