{"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/macro-grammars-and-holistic-triggering-for","title":"Macro Grammars and Holistic Triggering for Efficient Semantic Parsing","arxiv_id":"1707.07806","date":"2017-07-25","proceeding":"EMNLP 2017 9","authors":["Yuchen Zhang","Panupong Pasupat","Percy Liang"],"abstract":"To learn a semantic parser from denotations, a learning algorithm must search\nover a combinatorially large space of logical forms for ones consistent with\nthe annotated denotations. We propose a new online learning algorithm that\nsearches faster as training progresses. The two key ideas are using macro\ngrammars to cache the abstract patterns of useful logical forms found thus far,\nand holistic triggering to efficiently retrieve the most relevant patterns\nbased on sentence similarity. On the WikiTableQuestions dataset, we first\nexpand the search space of an existing model to improve the state-of-the-art\naccuracy from 38.7% to 42.7%, and then use macro grammars and holistic\ntriggering to achieve an 11x speedup and an accuracy of 43.7%.","url_abs":"http://arxiv.org/abs/1707.07806v2","url_pdf":"http://arxiv.org/pdf/1707.07806v2.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":"macro-grammars-and-holistic-triggering-for","repo_url":"https://github.com/percyliang/sempre","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"macro-grammars-and-holistic-triggering-for","repo_url":"https://worksheets.codalab.org/worksheets/0x4d6dbfc5ec7f44a6a4da4ca2a9334d6e","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"semantic-parsing","task_name":"Semantic Parsing"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"sentence-similarity","task_name":"Sentence Similarity"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1707.07806","atlas_url":"https://app.syntology.ai/?focus=1707.07806","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}