A Comprehensive Survey of Document-level Relation Extraction (2016-2023)
September 28, 2023 ยท The Cartographer ยท ๐ arXiv.org
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"Title-pattern auto-detect: A Comprehensive Survey of Document-level Relation Extraction (2016-2023)"
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Authors
Julien Delaunay, Hanh Thi Hong Tran, Carlos-Emiliano Gonzรกlez-Gallardo, Georgeta Bordea, Nicolas Sidere, Antoine Doucet
arXiv ID
2309.16396
Category
cs.CL: Computation & Language
Citations
8
Venue
arXiv.org
Last Checked
3 days ago
Abstract
Document-level relation extraction (DocRE) is an active area of research in natural language processing (NLP) concerned with identifying and extracting relationships between entities beyond sentence boundaries. Compared to the more traditional sentence-level relation extraction, DocRE provides a broader context for analysis and is more challenging because it involves identifying relationships that may span multiple sentences or paragraphs. This task has gained increased interest as a viable solution to build and populate knowledge bases automatically from unstructured large-scale documents (e.g., scientific papers, legal contracts, or news articles), in order to have a better understanding of relationships between entities. This paper aims to provide a comprehensive overview of recent advances in this field, highlighting its different applications in comparison to sentence-level relation extraction.
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