{"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/identifying-well-formed-natural-language","title":"Identifying Well-formed Natural Language Questions","arxiv_id":"1808.09419","date":"2018-08-28","proceeding":"EMNLP 2018 10","authors":["Manaal Faruqui","Dipanjan Das"],"abstract":"Understanding search queries is a hard problem as it involves dealing with\n\"word salad\" text ubiquitously issued by users. However, if a query resembles a\nwell-formed question, a natural language processing pipeline is able to perform\nmore accurate interpretation, thus reducing downstream compounding errors.\nHence, identifying whether or not a query is well formed can enhance query\nunderstanding. Here, we introduce a new task of identifying a well-formed\nnatural language question. We construct and release a dataset of 25,100\npublicly available questions classified into well-formed and non-wellformed\ncategories and report an accuracy of 70.7% on the test set. We also show that\nour classifier can be used to improve the performance of neural\nsequence-to-sequence models for generating questions for reading comprehension.","url_abs":"http://arxiv.org/abs/1808.09419v1","url_pdf":"http://arxiv.org/pdf/1808.09419v1.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":"identifying-well-formed-natural-language","repo_url":"https://github.com/google-research-datasets/query-wellformedness","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"query-wellformedness","task_name":"Query Wellformedness"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/query-wellformedness-on-query-wellformedness","task":"Query Wellformedness","dataset":"Query Wellformedness","model":"word-1, 2 POS-1, 2, 3","rank_in_archive_order":1,"of":1,"metrics":{"Accuracy":"70.7"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1808.09419","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}