{"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/incorporating-temporal-information-in","title":"Incorporating Temporal Information in Entailment Graph Mining","arxiv_id":"2109.09412","date":"2021-09-20","proceeding":"COLING (TextGraphs) 2020 12","authors":["Liane Guillou","Sander Bijl de Vroe","Mohammad Javad Hosseini","Mark Johnson","Mark Steedman"],"abstract":"We present a novel method for injecting temporality into entailment graphs to address the problem of spurious entailments, which may arise from similar but temporally distinct events involving the same pair of entities. We focus on the sports domain in which the same pairs of teams play on different occasions, with different outcomes. We present an unsupervised model that aims to learn entailments such as win/lose $\\rightarrow$ play, while avoiding the pitfall of learning non-entailments such as win $\\not\\rightarrow$ lose. We evaluate our model on a manually constructed dataset, showing that incorporating time intervals and applying a temporal window around them, are effective strategies.","url_abs":"https://arxiv.org/abs/2109.09412v1","url_pdf":"https://arxiv.org/pdf/2109.09412v1.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":"incorporating-temporal-information-in","repo_url":"https://gitlab.com/lianeg/temporal-entailment-sports-dataset","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"graph-mining","task_name":"Graph Mining"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2109.09412","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}