Abstract
Despite the significant progress on entity coreference resolution observed in recent years, there is a general lack of understanding of what has been improved. We present an empirical analysis of state-of-the-art resolvers with the goal of providing the general NLP audience with a better understanding of the state of the art and coreference researchers with directions for future research.
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CITATION STYLE
Lu, J., & Ng, V. (2020). Conundrums in entity coreference resolution: Making sense of the state of the art. In EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference (pp. 6620–6631). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2020.emnlp-main.536
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