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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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