{"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/event2mind-for-russian-understanding-emotions","title":"Event2Mind for Russian: Understanding Emotions and Intents in Texts. Corpus and Model for Evaluation","arxiv_id":null,"date":"2020-06-17","proceeding":"Computational Linguistics and Intellectual Technologies: Proceedings of the International Conference “Dialogue 2020” 2020 6","authors":["Fenogenova A. S.","Tikhonova M. I.","Filipetskaya D. V.","Mironenko F. D.","Tabisheva A. O"],"abstract":"The paper provides a comprehensive overview of the corpus for the Russian language for the commonsense inference task. Namely, we construct event phrases, which cover a wide range of everyday situations with labelled intents and reactions of the event main participant and emotions of other people involved. The dataset consists of two parts: a crowdsourced corpus of 6,756 examples from Russian sources and a translated into Russian part of the original corpus of 23,409 examples. Apart from this, we use the collected data in order to train the event2mind model for the Russian language. \r\nThe paper presents careful description of the best Russian model and the results of the conducted experiments.","url_abs":"http://www.dialog-21.ru/media/5090/fenogenovaasplusetal-010.pdf","url_pdf":"http://www.dialog-21.ru/media/5090/fenogenovaasplusetal-010.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":"event2mind-for-russian-understanding-emotions","repo_url":"https://github.com/Alenush/russian_event2mind","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"common-sense-reasoning","task_name":"Common Sense Reasoning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/common-sense-reasoning-on-russian-event2mind","task":"Common Sense Reasoning","dataset":"Russian Event2Mind","model":"araneum word2vec (skipgram) + GRU","rank_in_archive_order":1,"of":7,"metrics":{"recall@10":"0.827"},"uses_additional_data":false},{"leaderboard":"/sota/common-sense-reasoning-on-russian-event2mind","task":"Common Sense Reasoning","dataset":"Russian Event2Mind","model":"ruscorpora word2vec (skipgram) + GRU","rank_in_archive_order":2,"of":7,"metrics":{"recall@10":"0.825"},"uses_additional_data":false},{"leaderboard":"/sota/common-sense-reasoning-on-russian-event2mind","task":"Common Sense Reasoning","dataset":"Russian Event2Mind","model":"ruscorpora fasttext + GRU","rank_in_archive_order":3,"of":7,"metrics":{"recall@10":"0.822"},"uses_additional_data":false},{"leaderboard":"/sota/common-sense-reasoning-on-russian-event2mind","task":"Common Sense Reasoning","dataset":"Russian Event2Mind","model":"ruscorpora fasttext + LSTM","rank_in_archive_order":4,"of":7,"metrics":{"recall@10":"0.821"},"uses_additional_data":false},{"leaderboard":"/sota/common-sense-reasoning-on-russian-event2mind","task":"Common Sense Reasoning","dataset":"Russian Event2Mind","model":"araneum fasttext + GRU","rank_in_archive_order":5,"of":7,"metrics":{"recall@10":"0.819"},"uses_additional_data":false},{"leaderboard":"/sota/common-sense-reasoning-on-russian-event2mind","task":"Common Sense Reasoning","dataset":"Russian Event2Mind","model":"araneum fasttext + LSTM","rank_in_archive_order":6,"of":7,"metrics":{"recall@10":"0.818"},"uses_additional_data":false},{"leaderboard":"/sota/common-sense-reasoning-on-russian-event2mind","task":"Common Sense Reasoning","dataset":"Russian Event2Mind","model":"araneum word2vec (skipgram) + LSTM","rank_in_archive_order":7,"of":7,"metrics":{"recall@10":"0.816"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}