{"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/a-dataset-for-resolving-referring-expressions","title":"A dataset for resolving referring expressions in spoken dialogue via contextual query rewrites (CQR)","arxiv_id":"1903.11783","date":"2019-03-28","proceeding":null,"authors":["Michael Regan","Pushpendre Rastogi","Arpit Gupta","Lambert Mathias"],"abstract":"We present Contextual Query Rewrite (CQR) a dataset for multi-domain\ntask-oriented spoken dialogue systems that is an extension of the Stanford\ndialog corpus (Eric et al., 2017a). While previous approaches have addressed\nthe issue of diverse schemas by learning candidate transformations (Naik et\nal., 2018), we instead model the reference resolution task as a user query\nreformulation task, where the dialog state is serialized into a natural\nlanguage query that can be executed by the downstream spoken language\nunderstanding system. In this paper, we describe our methodology for creating\nthe query reformulation extension to the dialog corpus, and present an initial\nset of experiments to establish a baseline for the CQR task. We have released\nthe corpus to the public [1] to support further research in this area.","url_abs":"http://arxiv.org/abs/1903.11783v3","url_pdf":"http://arxiv.org/pdf/1903.11783v3.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":"a-dataset-for-resolving-referring-expressions","repo_url":"https://github.com/alexa/alexa-dataset-contextual-query-rewrite","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"spoken-dialogue-systems","task_name":"Spoken Dialogue Systems"},{"task_slug":"spoken-language-understanding","task_name":"Spoken Language Understanding"}],"methods":[],"datasets_introduced":[{"slug":"cqr","name":"CQR","full_name":"Contextual Query Rewrite"}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1903.11783","atlas_url":"https://app.syntology.ai/?focus=1903.11783","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}