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AmbigDocs: Reasoning across Documents on Different Entities under the Same Name
April 22, 2024, 4:46 a.m. | Yoonsang Lee, Xi Ye, Eunsol Choi
cs.CL updates on arXiv.org arxiv.org
Abstract: Different entities with the same name can be difficult to distinguish. Handling confusing entity mentions is a crucial skill for language models (LMs). For example, given the question "Where was Michael Jordan educated?" and a set of documents discussing different people named Michael Jordan, can LMs distinguish entity mentions to generate a cohesive answer to the question? To test this ability, we introduce a new benchmark, AmbigDocs. By leveraging Wikipedia's disambiguation pages, we identify a …
abstract arxiv cs.cl documents example language language models lms michael jordan people question reasoning set type
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