{"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/sequence-to-sequence-learning-for-event","title":"Sequence to Sequence Learning for Event Prediction","arxiv_id":"1709.06033","date":"2017-09-18","proceeding":"IJCNLP 2017 11","authors":["Dai Quoc Nguyen","Dat Quoc Nguyen","Cuong Xuan Chu","Stefan Thater","Manfred Pinkal"],"abstract":"This paper presents an approach to the task of predicting an event\ndescription from a preceding sentence in a text. Our approach explores\nsequence-to-sequence learning using a bidirectional multi-layer recurrent\nneural network. Our approach substantially outperforms previous work in terms\nof the BLEU score on two datasets derived from WikiHow and DeScript\nrespectively. Since the BLEU score is not easy to interpret as a measure of\nevent prediction, we complement our study with a second evaluation that\nexploits the rich linguistic annotation of gold paraphrase sets of events.","url_abs":"http://arxiv.org/abs/1709.06033v1","url_pdf":"http://arxiv.org/pdf/1709.06033v1.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":"sequence-to-sequence-learning-for-event","repo_url":"https://github.com/daiquocnguyen/EventPrediction","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"prediction","task_name":"Prediction"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1709.06033","atlas_url":"https://app.syntology.ai/?focus=1709.06033","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}