{"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/facts-that-matter","title":"Facts That Matter","arxiv_id":null,"date":"2018-10-01","proceeding":"EMNLP 2018 10","authors":["Marco Ponza","Luciano del Corro","Gerhard Weikum"],"abstract":"This work introduces fact salience: The task of generating a machine-readable representation of the most prominent information in a text document as a set of facts. We also present SalIE, the first fact salience system. SalIE is unsupervised and knowledge agnostic, based on open information extraction to detect facts in natural language text, PageRank to determine their relevance, and clustering to promote diversity. We compare SalIE with several baselines (including positional, standard for saliency tasks), and in an extrinsic evaluation, with state-of-the-art automatic text summarizers. SalIE outperforms baselines and text summarizers showing that facts are an effective way to compress information.","url_abs":"https://aclanthology.org/D18-1129","url_pdf":"https://aclanthology.org/D18-1129.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":"facts-that-matter","repo_url":"https://github.com/mponza/SalIE","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"diversity","task_name":"Diversity"},{"task_slug":"entity-linking","task_name":"Entity Linking"},{"task_slug":"open-information-extraction","task_name":"Open Information Extraction"},{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"relation-extraction","task_name":"Relation Extraction"},{"task_slug":"text-summarization","task_name":"Text Summarization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}