Dataset Card for d0rj/conv_ai_3_ru

Dataset Summary

This is translated version of conv_ai_3 dataset to Russian language.

Languages

Russian (translated from English).

Dataset Structure

Data Fields

• topic_id: the ID of the topic (initial_request).
• initial_request: the query (text) that initiates the conversation.
• topic_desc: a full description of the topic as it appears in the TREC Web Track data.
• clarification_need: a label from 1 to 4, indicating how much it is needed to clarify a topic. If an initial_request is self-contained and would not need any clarification, the label would be 1. While if a initial_request is absolutely ambiguous, making it impossible for a search engine to guess the user's right intent before clarification, the label would be 4.
• facet_id: the ID of the facet.
• facet_desc: a full description of the facet (information need) as it appears in the TREC Web Track data.
• question_id: the ID of the question..
• question: a clarifying question that the system can pose to the user for the current topic and facet.
• answer: an answer to the clarifying question, assuming that the user is in the context of the current row (i.e., the user's initial query is initial_request, their information need is facet_desc, and question has been posed to the user).

Citation Information

@misc{aliannejadi2020convai3, title={ConvAI3: Generating Clarifying Questions for Open-Domain Dialogue Systems (ClariQ)}, author={Mohammad Aliannejadi and Julia Kiseleva and Aleksandr Chuklin and Jeff Dalton and Mikhail Burtsev}, year={2020}, eprint={2009.11352}, archivePrefix={arXiv}, primaryClass={cs.CL} }

Contributions

Thanks to @rkc007 for adding this dataset.