{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/sire-separate-intra-and-inter-sentential","title":"SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation Extraction","arxiv_id":"2106.01709","date":"2021-06-03","proceeding":"Findings (ACL) 2021 8","authors":["Shuang Zeng","Yuting Wu","Baobao Chang"],"abstract":"Document-level relation extraction has attracted much attention in recent years. It is usually formulated as a classification problem that predicts relations for all entity pairs in the document. However, previous works indiscriminately represent intra- and inter-sentential relations in the same way, confounding the different patterns for predicting them. Besides, they create a document graph and use paths between entities on the graph as clues for logical reasoning. However, not all entity pairs can be connected with a path and have the correct logical reasoning paths in their graph. Thus many cases of logical reasoning cannot be covered. This paper proposes an effective architecture, SIRE, to represent intra- and inter-sentential relations in different ways. We design a new and straightforward form of logical reasoning module that can cover more logical reasoning chains. Experiments on the public datasets show SIRE outperforms the previous state-of-the-art methods. Further analysis shows that our predictions are reliable and explainable. Our code is available at https://github.com/DreamInvoker/SIRE.","url_abs":"https://arxiv.org/abs/2106.01709v1","url_pdf":"https://arxiv.org/pdf/2106.01709v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"sire-separate-intra-and-inter-sentential","repo_url":"https://github.com/DreamInvoker/SIRE","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"document-level-relation-extraction","task_name":"Document-level Relation Extraction"},{"task_slug":"logical-reasoning","task_name":"Logical Reasoning"},{"task_slug":null,"task_name":"Relation"},{"task_slug":"relation-extraction","task_name":"Relation Extraction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/relation-extraction-on-docred","task":"Relation Extraction","dataset":"DocRED","model":"SIRE-BERT-base","rank_in_archive_order":19,"of":62,"metrics":{"F1":"62.05","Ign F1":"60.18"},"uses_additional_data":false},{"leaderboard":"/sota/relation-extraction-on-docred","task":"Relation Extraction","dataset":"DocRED","model":"SIRE-GloVe","rank_in_archive_order":49,"of":62,"metrics":{"F1":"55.96","Ign F1":"54.04"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2106.01709","atlas_url":"https://app.syntology.ai/?focus=2106.01709","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}