← 返回资源分享
CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases
论文
论文
发布时间2019-09-11
发表IJCNLP 2019 11 · arXiv:1909.05378
作者:Caiming Xiong,Richard Socher,Walter S. Lasecki,Michihiro Yasunaga,Tao Yu,Rui Zhang,He Yang Er,Suyi Li,Eric Xue,Bo Pang,Xi Victoria Lin,Yi Chern Tan,Tianze Shi,Zihan Li,Youxuan Jiang,Sungrok Shim,Tao Chen,Alexander Fabbri,Zifan Li,Luyao Chen,Yuwen Zhang,Shreya Dixit,Vincent Zhang,Dragomir Radev
详细介绍
We present CoSQL, a corpus for building cross-domain, general-purpose database (DB) querying dialogue systems. It consists of 30k+ turns plus 10k+ annotated SQL queries, obtained from a Wizard-of-Oz (WOZ) collection of 3k dialogues querying 200 complex DBs spanning 138 domains. Each dialogue simulates a real-world DB query scenario with a crowd worker as a user exploring the DB and a SQL expert retrieving answers with SQL, clarifying ambiguous questions, or otherwise informing of unanswerable questions. When user questions are answerable by SQL, the expert describes the SQL and execution results to the user, hence maintaining a natural interaction flow. CoSQL introduces new challenges compared to existing task-oriented dialogue datasets:(1) the dialogue states are grounded in SQL, a domain-independent executable representation, instead of domain-specific slot-value pairs, and (2) because testing is done on unseen databases, success requires generalizing to new domains. CoSQL includes three tasks: SQL-grounded dialogue state tracking, response generation from query results, and user dialogue act prediction. We evaluate a set of strong baselines for each task and show that CoSQL presents significant challenges for future research. The dataset, baselines, and leaderboard will be released at https://yale-lily.github.io/cosql.
代码仓库 (4)
ryanzhumich/editsql官方PyTorch
ryanzhumich/sparc_atis_pytorchPyTorch
amolk/editsqlPyTorch
huseinzol05/malay-datasetTensorFlow
