{"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/dataset-for-a-neural-natural-language","title":"Dataset for a Neural Natural Language Interface for Databases (NNLIDB)","arxiv_id":"1707.03172","date":"2017-07-11","proceeding":"IJCNLP 2017 11","authors":["Florin Brad","Radu Iacob","Ionel Hosu","Traian Rebedea"],"abstract":"Progress in natural language interfaces to databases (NLIDB) has been slow\nmainly due to linguistic issues (such as language ambiguity) and domain\nportability. Moreover, the lack of a large corpus to be used as a standard\nbenchmark has made data-driven approaches difficult to develop and compare. In\nthis paper, we revisit the problem of NLIDBs and recast it as a sequence\ntranslation problem. To this end, we introduce a large dataset extracted from\nthe Stack Exchange Data Explorer website, which can be used for training neural\nnatural language interfaces for databases. We also report encouraging baseline\nresults on a smaller manually annotated test corpus, obtained using an\nattention-based sequence-to-sequence neural network.","url_abs":"http://arxiv.org/abs/1707.03172v1","url_pdf":"http://arxiv.org/pdf/1707.03172v1.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":"dataset-for-a-neural-natural-language","repo_url":"https://github.com/johnthebrave/nlidb-datasets","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1707.03172","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}