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arXiv · 2309.13249

A Survey of Document-Level Information Extraction

Hanwen Zheng·Sijia Wang·Lifu Huang
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Abstract

Document-level information extraction (IE) is a crucial task in natural language processing (NLP). This paper conducts a systematic review of recent document-level IE literature. In addition, we conduct a thorough error analysis with current state-of-the-art algorithms and identify their limitations as well as the remaining challenges for the task of document-level IE. According to our findings, labeling noises, entity coreference resolution, and lack of reasoning, severely affect the performance of document-level IE. The objective of this survey paper is to provide more insights and help NLP researchers to further enhance document-level IE performance.

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Hanwen Zheng, Sijia Wang, Lifu Huang. 2023-09-23. A Survey of Document-Level Information Extraction. https://arxiv.org/abs/2309.13249

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