Blindness to Modality Helps Entailment Graph Mining

Abstract

Understanding linguistic modality is widely seen as important for downstream tasks such as Question Answering and Knowledge Graph Population. Entailment Graph learning might also be expected to benefit from attention to modality. We build Entailment Graphs using a news corpus filtered with a modality parser, and show that stripping modal modifiers from predicates in fact increases performance. This suggests that for some tasks, the pragmatics of modal modification of predicates allows them to contribute as evidence of entailment.

Smoothing Entailment Graphs with Language Models

“…ANT. This is a new, high-quality dataset improving on Levy/Holt, which tests predicate entailment in the general domain (Guillou and Bijl de Vroe, 2023). It was created by expert annotation of entailment relations between clusters of predicate paraphrases, expanded automatically using WordNet and other dictionary resources into thousands of test questions of the format "given [premise], is [hypothesis] true?"…”