{"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/learning-distributed-representations-of-texts","title":"Learning Distributed Representations of Texts and Entities from Knowledge Base","arxiv_id":"1705.02494","date":"2017-05-06","proceeding":"TACL 2017 1","authors":["Ikuya Yamada","Hiroyuki Shindo","Hideaki Takeda","Yoshiyasu Takefuji"],"abstract":"We describe a neural network model that jointly learns distributed\nrepresentations of texts and knowledge base (KB) entities. Given a text in the\nKB, we train our proposed model to predict entities that are relevant to the\ntext. Our model is designed to be generic with the ability to address various\nNLP tasks with ease. We train the model using a large corpus of texts and their\nentity annotations extracted from Wikipedia. We evaluated the model on three\nimportant NLP tasks (i.e., sentence textual similarity, entity linking, and\nfactoid question answering) involving both unsupervised and supervised\nsettings. As a result, we achieved state-of-the-art results on all three of\nthese tasks. Our code and trained models are publicly available for further\nacademic research.","url_abs":"http://arxiv.org/abs/1705.02494v3","url_pdf":"http://arxiv.org/pdf/1705.02494v3.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":"learning-distributed-representations-of-texts","repo_url":"https://github.com/studio-ousia/ntee","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"entity-disambiguation","task_name":"Entity Disambiguation"},{"task_slug":"entity-linking","task_name":"Entity Linking"},{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/entity-disambiguation-on-aida-conll","task":"Entity Disambiguation","dataset":"AIDA-CoNLL","model":"NTEE","rank_in_archive_order":4,"of":20,"metrics":{"In-KB Accuracy":"94.7"},"uses_additional_data":false},{"leaderboard":"/sota/entity-disambiguation-on-tac2010","task":"Entity Disambiguation","dataset":"TAC2010","model":"NTEE","rank_in_archive_order":2,"of":4,"metrics":{"Micro Precision":"87.7"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1705.02494","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}