Computer Science > Computation and Language
[Submitted on 9 Oct 2023 (v1), last revised 19 Oct 2023 (this version, v2)]
Title:CAW-coref: Conjunction-Aware Word-level Coreference Resolution
View PDFAbstract:State-of-the-art coreference resolutions systems depend on multiple LLM calls per document and are thus prohibitively expensive for many use cases (e.g., information extraction with large corpora). The leading word-level coreference system (WL-coref) attains 96.6% of these SOTA systems' performance while being much more efficient. In this work, we identify a routine yet important failure case of WL-coref: dealing with conjoined mentions such as 'Tom and Mary'. We offer a simple yet effective solution that improves the performance on the OntoNotes test set by 0.9% F1, shrinking the gap between efficient word-level coreference resolution and expensive SOTA approaches by 34.6%. Our Conjunction-Aware Word-level coreference model (CAW-coref) and code is available at this https URL.
Submission history
From: Karel D'Oosterlinck [view email][v1] Mon, 9 Oct 2023 21:32:49 UTC (82 KB)
[v2] Thu, 19 Oct 2023 17:31:14 UTC (82 KB)
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