{"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/type-driven-incremental-semantic-parsing-with","title":"Type-Driven Incremental Semantic Parsing with Polymorphism","arxiv_id":"1411.5379","date":"2014-11-19","proceeding":"HLT 2015 5","authors":["Kai Zhao","Liang Huang"],"abstract":"Semantic parsing has made significant progress, but most current semantic\nparsers are extremely slow (CKY-based) and rather primitive in representation.\nWe introduce three new techniques to tackle these problems. First, we design\nthe first linear-time incremental shift-reduce-style semantic parsing algorithm\nwhich is more efficient than conventional cubic-time bottom-up semantic\nparsers. Second, our parser, being type-driven instead of syntax-driven, uses\ntype-checking to decide the direction of reduction, which eliminates the need\nfor a syntactic grammar such as CCG. Third, to fully exploit the power of\ntype-driven semantic parsing beyond simple types (such as entities and truth\nvalues), we borrow from programming language theory the concepts of subtype\npolymorphism and parametric polymorphism to enrich the type system in order to\nbetter guide the parsing. Our system learns very accurate parses in GeoQuery,\nJobs and Atis domains.","url_abs":"http://arxiv.org/abs/1411.5379v3","url_pdf":"http://arxiv.org/pdf/1411.5379v3.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":[],"tasks":[{"task_slug":"semantic-parsing","task_name":"Semantic Parsing"},{"task_slug":"type","task_name":"Vocal Bursts Type Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/semantic-parsing-on-atis","task":"Semantic Parsing","dataset":"ATIS","model":"ZH15 (Zhao and Huang, 2015)","rank_in_archive_order":4,"of":4,"metrics":{"Accuracy":"84.2"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1411.5379","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}