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"description": "RiSAWOZ contains 11.2K human-to-human (H2H) multiturn semantically annotated dialogues, with more than 150K utterances spanning over 12 domains, which is larger than all previous annotated H2H conversational datasets.Both single- and multi-domain dialogues are constructed, accounting for 65% and 35%, respectively.\n",
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"citation": "@inproceedings{quan-etal-2020-risawoz,\n title = \"{R}i{SAWOZ}: A Large-Scale Multi-Domain {W}izard-of-{O}z Dataset with Rich Semantic Annotations for Task-Oriented Dialogue Modeling\",\n author = \"Quan, Jun and\n Zhang, Shian and\n Cao, Qian and\n Li, Zizhong and\n Xiong, Deyi\",\n booktitle = \"Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)\",\n month = nov,\n year = \"2020\",\n address = \"Online\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/2020.emnlp-main.67\",\n pages = \"930--940\",\n}\n",
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"homepage": "https://github.com/terryqj0107/RiSAWOZ",
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"license": "Attribution 4.0 International (CC BY 4.0) license.",
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