Given a sentence "Abby told Brittney that she upset Courtney", one would struggle to understand who "she" refers to, and ask for clarification. However, if the word "upset" were replaced with "hugged", "she" unambiguously refers to Abby. We study if modern coreference resolution models are sensitive to such pronominal ambiguity. To this end, we construct AmbiCoref, a diagnostic corpus of minimal sentence pairs with ambiguous and unambiguous referents. Our examples generalize psycholinguistic studies of human perception of ambiguity around particular arrangements of verbs and their arguments. Analysis shows that (1) humans are less sure of referents in ambiguous AmbiCoref examples than unambiguous ones, and (2) most coreference models show little difference in output between ambiguous and unambiguous pairs. We release AmbiCoref as a diagnostic corpus for testing whether models treat ambiguity similarly to human.

通过构建一个名为AmbiCoref的语料库，将人类对于可替代性语言的理解问题推广至基于现代核心指代解析模型，分析展示了人类理解遇到歧义情况时的表现，以及现代解析模型处理歧义情况时的表现，最终将AmbiCoref作为一个测试工具发布出来。

AmbiCoref：评估人类和模型对模糊指代的敏感性