{"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/kptimes-a-large-scale-dataset-for-keyphrase-1","title":"KPTimes: A Large-Scale Dataset for Keyphrase Generation on News Documents","arxiv_id":"1911.12559","date":"2019-11-28","proceeding":"WS 2019 10","authors":["Ygor Gallina","Florian Boudin","Béatrice Daille"],"abstract":"Keyphrase generation is the task of predicting a set of lexical units that conveys the main content of a source text. Existing datasets for keyphrase generation are only readily available for the scholarly domain and include non-expert annotations. In this paper we present KPTimes, a large-scale dataset of news texts paired with editor-curated keyphrases. Exploring the dataset, we show how editors tag documents, and how their annotations differ from those found in existing datasets. We also train and evaluate state-of-the-art neural keyphrase generation models on KPTimes to gain insights on how well they perform on the news domain. The dataset is available online at https://github.com/ygorg/KPTimes .","url_abs":"https://arxiv.org/abs/1911.12559v1","url_pdf":"https://arxiv.org/pdf/1911.12559v1.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":"kptimes-a-large-scale-dataset-for-keyphrase-1","repo_url":"https://github.com/ygorg/KPTimes","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"keyphrase-generation","task_name":"Keyphrase Generation"},{"task_slug":"tag","task_name":"TAG"}],"methods":[],"datasets_introduced":[{"slug":"kptimes","name":"KPTimes","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1911.12559","atlas_url":"https://app.syntology.ai/?focus=1911.12559","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}