DoQA

DoQA is a dataset for accessing Domain Specific FAQs via conversational QA that contains 2,437 information-seeking question/answer dialogues (10,917 questions in total) on three different domains: cooking, travel and movies. Note that we include in the generic concept of FAQs also Community Question Answering sites, as well as corporate information in intranets which is maintained in textual form similar to FAQs, often referred to as internal “knowledge bases”. These dialogues are created by crowd workers that play the following two roles: the user who asks questions about a given topic posted in Stack Exchange (https://stackexchange.com/), and the domain expert who replies to the questions by selecting a short span of text from the long textual reply in the original post. The expert can rephrase the selected span, in order to make it look more natural. The dataset covers unanswerable questions and some relevant dialogue acts. DoQA enables the development and evaluation of conversational QA systems that help users access the knowledge buried in domain specific FAQs. If you are using this dataset in your work, please cite this publication:

J.A. Campos, A. Otegi, A. Soroa, J. Deriu, M. Cieliebak, E. Agirre. DoQA - Accessing Domain-Specific FAQs via Conversational QA. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 7302–7314. 2020.

Version 1.0 of the dataset is also available (see link above). In this case please cite this publication:

J.A. Campos, A. Otegi, A. Soroa, J. Deriu, M. Cieliebak, E. Agirre. Conversational QA for FAQs. Proceedings of NeurIPS 3rd Conversational AI Workshop: Today's Practice and Tomorrow's Potential. 2019.