A Comprehensive Survey of Document-level Relation Extraction (2016-2023)

September 28, 2023 ยท The Cartographer ยท ๐Ÿ› arXiv.org

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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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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