Conundrums in Entity Coreference Resolution: Making Sense of the State of the Art
Jing Lu, Vincent Ng
2020年份
13被引次数
4顶会引用
摘要
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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引用它的顶会 Paper4
- Incorporating Constituent Syntax for Coreference ResolutionFan Jiang, Trevor CohnAAAI 2022 · 被引用 6 次
- Major Entity Identification: A Generalizable Alternative to Coreference ResolutionKawshik Sundar, Shubham Toshniwal, Makarand Tapaswi, Vineet GandhiEMNLP 2024 · 被引用 4 次
- Annotating Mentions Alone Enables Efficient Domain Adaptation for Coreference ResolutionNupoor Gandhi, Anjalie Field, Emma StrubellACL 2023 · 被引用 3 次
- Entity-Based Knowledge Conflicts in Question AnsweringShayne Longpre, Kartik Perisetla, Anthony Chen, Nikhil Ramesh 等EMNLP 2021 · 被引用 3 次
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