The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
Deterministic Coreference Resolution Based on Entity-Centric, Precision-Ranked Rules
Abstract
We propose a new deterministic approach to coreference resolution that combines the global information and precise features of modern machine-learning models with the transparency and modularity of deterministic, rule-based systems. Our sieve architecture applies a battery of deterministic coreference models one at a time from highest to lowest precision, where each model builds on the previous model's cluster output. The two stages of our sieve-based architecture, a mention detection stage that heavily favors recall, followed by coreference sieves that are precision-oriented, offer a powerful way to achieve both high precision and high recall. Further, our approach makes use of global information through an entity-centric model that encourages the sharing of features across all mentions that point to the same real-world entity. Despite its simplicity, our approach gives state-of-the-art performance on several corpora and genres, and has also been incorporated into hybrid state-of-the-art coreference systems for Chinese and Arabic. Our system thus offers a new paradigm for combining knowledge in rule-based systems that has implications throughout computational linguistics.
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Cited by
Learning Everything about Anything: Webly-Supervised Visual Concept Learning
Divvala, S. K., Farhadi, A., & Guestrin, C. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.412 · Cited by 267
Mind the GAP: A balanced corpus of gendered ambiguous pronouns
Webster, K., Recasens, M., Axelrod, V., & Baldridge, J. (2018) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00240 · Cited by 223
Creative Help: A Story Writing Assistant
Roemmele, M., & Gordon, A. S. (2015) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-27036-4_8 · Cited by 83
LISA: Lexically Intelligent Story Assistant
Sanghrajka, R., Hidalgo, D., Chen, P., & Kapadia, M. (2017) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v13i1.12956 · Cited by 10
Metadata
- Authors
- Lee, H., Chang, A., Peirsman, Y., Chambers, N., Surdeanu, M., & Jurafsky, D.
- Venue
- Computational Linguistics
- Publisher
- MIT Press - Journals
- Published
- 2013-12
- Volume
- 39
- Issue
- 4
- Pages
- 885-916
- ISSN
- 0891-2017 (ISSN-L)
- 1530-9312
- OpenAlex
- W2147218300
- Cited by
- 384
- References
- 69
- FWCI
- 68.10
- Type
- journal article
- Language
- en
- Open access
- closed
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