{ "overview": { "where": { "has-leaderboard": "no", "leaderboard-url": "N/A", "leaderboard-description": "N/A", "website": "https://github.com/thu-coai/CrossWOZ", "data-url": "https://github.com/thu-coai/CrossWOZ", "paper-url": "https://aclanthology.org/2020.tacl-1.19.pdf", "paper-bibtext": "@article{zhu-etal-2020-crosswoz,\n title = \"{C}ross{WOZ}: A Large-Scale {C}hinese Cross-Domain Task-Oriented Dialogue Dataset\",\n author = \"Zhu, Qi and\n Huang, Kaili and\n Zhang, Zheng and\n Zhu, Xiaoyan and\n Huang, Minlie\",\n journal = \"Transactions of the Association for Computational Linguistics\",\n volume = \"8\",\n year = \"2020\",\n url = \"https://aclanthology.org/2020.tacl-1.19\",\n doi = \"10.1162/tacl_a_00314\",\n pages = \"281--295\",\n abstract = \"To advance multi-domain (cross-domain) dialogue modeling as well as alleviate the shortage of Chinese task-oriented datasets, we propose CrossWOZ, the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset. It contains 6K dialogue sessions and 102K utterances for 5 domains, including hotel, restaurant, attraction, metro, and taxi. Moreover, the corpus contains rich annotation of dialogue states and dialogue acts on both user and system sides. About 60{\\%} of the dialogues have cross-domain user goals that favor inter-domain dependency and encourage natural transition across domains in conversation. We also provide a user simulator and several benchmark models for pipelined task-oriented dialogue systems, which will facilitate researchers to compare and evaluate their models on this corpus. The large size and rich annotation of CrossWOZ make it suitable to investigate a variety of tasks in cross-domain dialogue modeling, such as dialogue state tracking, policy learning, user simulation, etc.\",\n}", "contact-name": "Qi Zhu", "contact-email": "zhuq96@gmail.com" }, "languages": { "is-multilingual": "no", "license": "apache-2.0: Apache License 2.0", "task-other": "N/A", "language-names": [ "Chinese" ], "license-other": "N/A", "intended-use": "CrossWOZ is the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset. It contains 6K dialogue sessions and 102K utterances for 5 domains, including hotel, restaurant, attraction, metro, and taxi. Moreover, the corpus contains rich annotation of dialogue states and dialogue acts at both user and system sides. We also provide a user simulator and several benchmark models for pipelined taskoriented dialogue systems, which will facilitate researchers to compare and evaluate their models on this corpus.", "task": "Dialog Response Generation", "communicative": "Generate a response according to the dialog context and database search results." }, "credit": { "organization-type": [ "academic" ], "organization-names": "Tsinghua University", "creators": "Qi Zhu, Kaili Huang, Zheng Zhang, Xiaoyan Zhu, and Minlie Huang from CoAI group, Tsinghua University", "funding": "National Science Foundation of China, National Key R&D Program of China ", "gem-added-by": "Qi Zhu (Tsinghua University)" }, "structure": { "data-fields": "- gem_id(string): GEM-CrossWOZ-{split}-{id}\n- dialog_id(string): dialog ID\n- sys_id(string): system annotator ID\n- usr_id(string): user annotation ID\n- type(string): dialog type\n- task description(list of strings): natural language descriptions of the user goal\n- goal(list of tuples), includes:\n - sub-goal id(string)\n - domain name(string)\n - slot name(string)\n - constraint if filled, else requirement(string)\n - whether be mentioned in previous turns(string)\n- messages(list of dict): dialog turns. Each turn contains:\n - content(string): utterance\n - role(string): user or system\n - dialog_act(list of tuples), includes:\n - domain(string)\n - intent(string)\n - slot(string)\n - value(string)\n - user_state(list of tuples): same format as \"goal\", can be viewed as dynamic goal.\n - sys_state_init(dict): the first db query emitted, records user constraints faithfully. If the system find no result that matches, he/she may relax the constraints manually and search db multiple times.\n - domain(dict): slot(string)-value(string) pairs\n - selectedResults(list of string): db search result that would be used in this turn.\n - sys_state(dict): the final db query emitted, records the db used by the system in this turn. Same format as sys_state_init. Note that this may not satisfy all user constraints.\n- final_goal(list of tuples): user state/goal at the end of dialog. same format as \"goal\".", "structure-description": "", "structure-labels": "", "structure-splits": "| Split | Train | Valid | Test |\n| --------------------- | ------ | ----- | ----- |\n| \\# dialogues | 5,012 | 500 | 500 |\n| \\# Turns (utterances) | 84,692 | 8,458 | 8,476 |\n| Vocab | 12,502 | 5,202 | 5,143 |\n| Avg. sub-goals | 3.24 | 3.26 | 3.26 |\n| Avg. semantic tuples | 14.8 | 14.9 | 15.0 |\n| Avg. turns | 16.9 | 16.9 | 17.0 |\n| Avg. tokens per turn | 16.3 | 16.3 | 16.2 |", "structure-example": "{'dialog_id': '2303',\n 'final_goal': [['1', '餐馆', '人均消费', '50-100元', 'True'],\n ['1', '餐馆', '推荐菜', \"['美食街']\", 'True'],\n ['1', '餐馆', '名称', '鲜鱼口老字号美食街', 'True'],\n ['1', '餐馆', '营业时间', '周一至周日 10:00-22:00', 'True'],\n ['1', '餐馆', '周边景点', \"['天安门广场', '前门大街', '恭王府', '故宫']\", 'True'],\n ['2', '景点', '名称', '故宫', 'True'],\n ['2', '景点', '评分', '4.5分以上', 'True'],\n ['2', '景点', '地址', '北京市东城区景山前街4号', 'True'],\n ['2', '景点', '电话', '010-85007938', 'True'],\n ['3', '酒店', '名称', '桔子水晶酒店(北京安贞店)', 'True'],\n ['3', '酒店', '电话', '010-84273030', 'True']],\n 'gem_id': 'GEM-CrossWOZ-test-0',\n 'goal': [['1', '餐馆', '人均消费', '50-100元', 'False'],\n ['1', '餐馆', '推荐菜', \"['美食街']\", 'False'],\n ['1', '餐馆', '名称', '', 'False'],\n ['1', '餐馆', '营业时间', '', 'False'],\n ['1', '餐馆', '周边景点', '[]', 'False'],\n ['2', '景点', '名称', '出现在id=1的周边景点里', 'False'],\n ['2', '景点', '评分', '4.5分以上', 'False'],\n ['2', '景点', '地址', '', 'False'],\n ['2', '景点', '电话', '', 'False'],\n ['3', '酒店', '名称', '桔子水晶酒店(北京安贞店)', 'False'],\n ['3', '酒店', '电话', '', 'False']],\n 'messages': {'content': ['你好,我想吃美食街,帮我推荐一个人均消费在50-100元的餐馆,谢谢。',\n '为您推荐鲜鱼口老字号美食街,人均消费75元,有您想吃的美食街哦。',\n '营业时间是什么时间?',\n '周一至周日 10:00-22:00。',\n '他家周边有什么景点吗?',\n '有故宫, 前门大街, 恭王府, 天安门广场。',\n '哦,我想在这些附近景点里找一个4.5分以上的,有吗?',\n '故宫就是哦,4.7分。',\n '好的,电话和地址告诉我一下。',\n '010-85007938;北京市东城区景山前街4号。',\n '好的,麻烦你帮我查一下桔子水晶酒店(北京安贞店)电话呗。',\n '010-84273030。',\n '好的,收到,谢谢你!',\n '不客气。'],\n 'dialog_act': [[['General', 'greet', 'none', 'none'],\n ['General', 'thank', 'none', 'none'],\n ['Inform', '餐馆', '人均消费', '50-100元'],\n ['Inform', '餐馆', '推荐菜', '美食街'],\n ['Request', '餐馆', '名称', '']],\n [['Inform', '餐馆', '人均消费', '75元'], ['Inform', '餐馆', '名称', '鲜鱼口老字号美食街']],\n [['Request', '餐馆', '营业时间', '']],\n [['Inform', '餐馆', '营业时间', '周一至周日 10:00-22:00']],\n [['Request', '餐馆', '周边景点', '']],\n [['Inform', '餐馆', '周边景点', '前门大街'],\n ['Inform', '餐馆', '周边景点', '天安门广场'],\n ['Inform', '餐馆', '周边景点', '恭王府'],\n ['Inform', '餐馆', '周边景点', '故宫']],\n [['Inform', '景点', '评分', '4.5分以上'], ['Select', '景点', '源领域', '餐馆']],\n [['Inform', '景点', '名称', '故宫'], ['Inform', '景点', '评分', '4.7分']],\n [['Request', '景点', '地址', ''], ['Request', '景点', '电话', '']],\n [['Inform', '景点', '地址', '北京市东城区景山前街4号'],\n ['Inform', '景点', '电话', '010-85007938']],\n [['Inform', '酒店', '名称', '桔子水晶酒店(北京安贞店)'], ['Request', '酒店', '电话', '']],\n [['Inform', '酒店', '电话', '010-84273030']],\n [['General', 'thank', 'none', 'none']],\n [['General', 'welcome', 'none', 'none']]],\n 'role': ['usr',\n 'sys',\n 'usr',\n 'sys',\n 'usr',\n 'sys',\n 'usr',\n 'sys',\n 'usr',\n 'sys',\n 'usr',\n 'sys',\n 'usr',\n 'sys'],\n 'sys_state': [{'出租': {'selectedResults': [], '出发地': '', '目的地': ''},\n '地铁': {'selectedResults': [], '出发地': '', '目的地': ''},\n '景点': {'selectedResults': [],\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '游玩时间': '',\n '评分': '',\n '门票': ''},\n '酒店': {'selectedResults': [],\n '价格': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '评分': '',\n '酒店类型': '',\n '酒店设施': ''},\n '餐馆': {'selectedResults': [],\n '人均消费': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '推荐菜': '',\n '评分': ''}},\n {'出租': {'selectedResults': [], '出发地': '', '目的地': ''},\n '地铁': {'selectedResults': [], '出发地': '', '目的地': ''},\n '景点': {'selectedResults': [],\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '游玩时间': '',\n '评分': '',\n '门票': ''},\n '酒店': {'selectedResults': [],\n '价格': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '评分': '',\n '酒店类型': '',\n '酒店设施': ''},\n '餐馆': {'selectedResults': ['鲜鱼口老字号美食街'],\n '人均消费': '50-100元',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '推荐菜': '美食街',\n '评分': ''}},\n {'出租': {'selectedResults': [], '出发地': '', '目的地': ''},\n '地铁': {'selectedResults': [], '出发地': '', '目的地': ''},\n '景点': {'selectedResults': [],\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '游玩时间': '',\n '评分': '',\n '门票': ''},\n '酒店': {'selectedResults': [],\n '价格': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '评分': '',\n '酒店类型': '',\n '酒店设施': ''},\n '餐馆': {'selectedResults': [],\n '人均消费': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '推荐菜': '',\n '评分': ''}},\n {'出租': {'selectedResults': [], '出发地': '', '目的地': ''},\n '地铁': {'selectedResults': [], '出发地': '', '目的地': ''},\n '景点': {'selectedResults': [],\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '游玩时间': '',\n '评分': '',\n '门票': ''},\n '酒店': {'selectedResults': [],\n '价格': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '评分': '',\n '酒店类型': '',\n '酒店设施': ''},\n '餐馆': {'selectedResults': ['鲜鱼口老字号美食街'],\n '人均消费': '50-100元',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '推荐菜': '美食街',\n '评分': ''}},\n {'出租': {'selectedResults': [], '出发地': '', '目的地': ''},\n '地铁': {'selectedResults': [], '出发地': '', '目的地': ''},\n '景点': {'selectedResults': [],\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '游玩时间': '',\n '评分': '',\n '门票': ''},\n '酒店': {'selectedResults': [],\n '价格': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '评分': '',\n '酒店类型': '',\n '酒店设施': ''},\n '餐馆': {'selectedResults': [],\n '人均消费': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '推荐菜': '',\n '评分': ''}},\n {'出租': {'selectedResults': [], '出发地': '', '目的地': ''},\n '地铁': {'selectedResults': [], '出发地': '', '目的地': ''},\n '景点': {'selectedResults': [],\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '游玩时间': '',\n '评分': '',\n '门票': ''},\n '酒店': {'selectedResults': [],\n '价格': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '评分': '',\n '酒店类型': '',\n '酒店设施': ''},\n '餐馆': {'selectedResults': ['鲜鱼口老字号美食街'],\n '人均消费': '50-100元',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '推荐菜': '美食街',\n '评分': ''}},\n {'出租': {'selectedResults': [], '出发地': '', '目的地': ''},\n '地铁': {'selectedResults': [], '出发地': '', '目的地': ''},\n '景点': {'selectedResults': [],\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '游玩时间': '',\n '评分': '',\n '门票': ''},\n '酒店': {'selectedResults': [],\n '价格': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '评分': '',\n '酒店类型': '',\n '酒店设施': ''},\n '餐馆': {'selectedResults': [],\n '人均消费': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '推荐菜': '',\n '评分': ''}},\n {'出租': {'selectedResults': [], '出发地': '', '目的地': ''},\n '地铁': {'selectedResults': [], '出发地': '', '目的地': ''},\n '景点': {'selectedResults': ['故宫'],\n '名称': '故宫',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '游玩时间': '',\n '评分': '',\n '门票': ''},\n '酒店': {'selectedResults': [],\n '价格': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '评分': '',\n '酒店类型': '',\n '酒店设施': ''},\n '餐馆': {'selectedResults': [],\n '人均消费': '50-100元',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '推荐菜': '美食街',\n '评分': ''}},\n {'出租': {'selectedResults': [], '出发地': '', '目的地': ''},\n '地铁': {'selectedResults': [], '出发地': '', '目的地': ''},\n '景点': {'selectedResults': [],\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '游玩时间': '',\n '评分': '',\n '门票': ''},\n '酒店': {'selectedResults': [],\n '价格': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '评分': '',\n '酒店类型': '',\n '酒店设施': ''},\n '餐馆': {'selectedResults': [],\n '人均消费': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '推荐菜': '',\n '评分': ''}},\n {'出租': {'selectedResults': [], '出发地': '', '目的地': ''},\n '地铁': {'selectedResults': [], '出发地': '', '目的地': ''},\n '景点': {'selectedResults': ['故宫'],\n '名称': '故宫',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': 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'餐馆': {'selectedResults': [],\n '人均消费': '',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '推荐菜': '',\n '评分': ''}},\n {'出租': {'selectedResults': [], '出发地': '', '目的地': ''},\n '地铁': {'selectedResults': [], '出发地': '', '目的地': ''},\n '景点': {'selectedResults': [],\n '名称': '故宫',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '游玩时间': '',\n '评分': '',\n '门票': ''},\n '酒店': {'selectedResults': ['桔子水晶酒店(北京安贞店)'],\n '价格': '',\n '名称': '桔子水晶酒店(北京安贞店)',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '评分': '',\n '酒店类型': '',\n '酒店设施': ''},\n '餐馆': {'selectedResults': [],\n '人均消费': '50-100元',\n '名称': '',\n '周边景点': '',\n '周边酒店': '',\n '周边餐馆': '',\n '推荐菜': '美食街',\n '评分': ''}}],\n 'user_state': [[['1', '餐馆', '人均消费', '50-100元', 'True'],\n ['1', '餐馆', '推荐菜', \"['美食街']\", 'True'],\n ['1', '餐馆', '名称', '', 'True'],\n ['1', '餐馆', '营业时间', '', 'False'],\n ['1', '餐馆', '周边景点', '[]', 'False'],\n ['2', '景点', '名称', '出现在id=1的周边景点里', 'False'],\n ['2', '景点', '评分', '4.5分以上', 'False'],\n ['2', '景点', '地址', '', 'False'],\n ['2', '景点', '电话', '', 'False'],\n ['3', '酒店', '名称', '桔子水晶酒店(北京安贞店)', 'False'],\n ['3', '酒店', '电话', '', 'False']],\n [],\n [['1', '餐馆', '人均消费', '50-100元', 'True'],\n ['1', '餐馆', '推荐菜', \"['美食街']\", 'True'],\n ['1', '餐馆', '名称', '鲜鱼口老字号美食街', 'True'],\n ['1', '餐馆', '营业时间', '', 'True'],\n ['1', '餐馆', '周边景点', '[]', 'False'],\n ['2', '景点', '名称', '出现在id=1的周边景点里', 'False'],\n ['2', '景点', '评分', '4.5分以上', 'False'],\n ['2', '景点', '地址', '', 'False'],\n ['2', '景点', '电话', '', 'False'],\n ['3', '酒店', '名称', '桔子水晶酒店(北京安贞店)', 'False'],\n ['3', '酒店', '电话', '', 'False']],\n [],\n [['1', '餐馆', '人均消费', '50-100元', 'True'],\n ['1', '餐馆', '推荐菜', \"['美食街']\", 'True'],\n ['1', '餐馆', '名称', '鲜鱼口老字号美食街', 'True'],\n ['1', '餐馆', '营业时间', '周一至周日 10:00-22:00', 'True'],\n ['1', '餐馆', '周边景点', '[]', 'True'],\n ['2', '景点', '名称', '出现在id=1的周边景点里', 'False'],\n ['2', '景点', '评分', '4.5分以上', 'False'],\n ['2', '景点', '地址', '', 'False'],\n ['2', '景点', '电话', '', 'False'],\n ['3', '酒店', '名称', '桔子水晶酒店(北京安贞店)', 'False'],\n ['3', '酒店', '电话', '', 'False']],\n [],\n [['1', '餐馆', '人均消费', '50-100元', 'True'],\n ['1', '餐馆', '推荐菜', \"['美食街']\", 'True'],\n ['1', '餐馆', '名称', '鲜鱼口老字号美食街', 'True'],\n ['1', '餐馆', '营业时间', '周一至周日 10:00-22:00', 'True'],\n ['1', '餐馆', '周边景点', \"['天安门广场', '前门大街', '恭王府', '故宫']\", 'True'],\n ['2', '景点', '名称', '出现在id=1的周边景点里', 'True'],\n ['2', '景点', '评分', '4.5分以上', 'True'],\n ['2', '景点', '地址', '', 'False'],\n ['2', '景点', '电话', '', 'False'],\n ['3', '酒店', '名称', '桔子水晶酒店(北京安贞店)', 'False'],\n ['3', '酒店', '电话', '', 'False']],\n [],\n [['1', '餐馆', '人均消费', '50-100元', 'True'],\n ['1', '餐馆', '推荐菜', \"['美食街']\", 'True'],\n ['1', '餐馆', '名称', '鲜鱼口老字号美食街', 'True'],\n ['1', '餐馆', '营业时间', '周一至周日 10:00-22:00', 'True'],\n ['1', '餐馆', '周边景点', \"['天安门广场', '前门大街', '恭王府', '故宫']\", 'True'],\n ['2', '景点', '名称', '故宫', 'True'],\n ['2', '景点', '评分', '4.5分以上', 'True'],\n ['2', '景点', '地址', '', 'True'],\n ['2', '景点', '电话', '', 'True'],\n ['3', '酒店', '名称', '桔子水晶酒店(北京安贞店)', 'False'],\n ['3', '酒店', '电话', '', 'False']],\n [],\n [['1', '餐馆', '人均消费', '50-100元', 'True'],\n ['1', '餐馆', '推荐菜', \"['美食街']\", 'True'],\n ['1', '餐馆', '名称', '鲜鱼口老字号美食街', 'True'],\n ['1', '餐馆', '营业时间', '周一至周日 10:00-22:00', 'True'],\n ['1', '餐馆', '周边景点', \"['天安门广场', '前门大街', '恭王府', '故宫']\", 'True'],\n ['2', '景点', '名称', '故宫', 'True'],\n ['2', '景点', '评分', '4.5分以上', 'True'],\n ['2', '景点', '地址', '北京市东城区景山前街4号', 'True'],\n ['2', '景点', '电话', '010-85007938', 'True'],\n ['3', '酒店', '名称', '桔子水晶酒店(北京安贞店)', 'True'],\n ['3', '酒店', '电话', '', 'True']],\n [],\n [['1', '餐馆', '人均消费', '50-100元', 'True'],\n ['1', '餐馆', '推荐菜', \"['美食街']\", 'True'],\n ['1', '餐馆', '名称', '鲜鱼口老字号美食街', 'True'],\n ['1', '餐馆', '营业时间', '周一至周日 10:00-22:00', 'True'],\n ['1', '餐馆', '周边景点', \"['天安门广场', '前门大街', '恭王府', '故宫']\", 'True'],\n ['2', '景点', '名称', '故宫', 'True'],\n ['2', '景点', '评分', '4.5分以上', 'True'],\n ['2', '景点', '地址', '北京市东城区景山前街4号', 'True'],\n ['2', '景点', '电话', '010-85007938', 'True'],\n ['3', '酒店', '名称', '桔子水晶酒店(北京安贞店)', 'True'],\n ['3', '酒店', '电话', '010-84273030', 'True']],\n []]},\n 'sys_id': 96,\n 'task description': ['你要去一个餐馆(id=1)用餐。你希望餐馆的人均消费是50-100元的。你想吃的菜肴是美食街。你想知道这个餐馆的名称、营业时间、周边景点。',\n '你要去id=1附近的景点(id=2)游玩。你希望景点的评分是4.5分以上。你想知道这个景点的地址、电话。',\n '你要去名叫桔子水晶酒店(北京安贞店)的酒店(id=3)住宿。你想知道这个酒店的电话。'],\n 'type': '不独立多领域',\n 'usr_id': 97}", "structure-splits-criteria": "", "structure-outlier": "" } }, "context": { "previous": { "is-deployed": "no", "described-risks": "N/A", "changes-from-observation": "N/A" }, "underserved": { "helps-underserved": "yes", "underserved-description": "CrossWOZ is the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset. The corpus contains rich annotation of dialogue states and dialogue acts at both user and system sides, which can be used in a wide range of tasks." }, "biases": { "has-biases": "no", "bias-analyses": "N/A", "speaker-distibution": "Yes" } }, "considerations": { "pii": { "risks-description": "No" }, "licenses": { "dataset-restrictions-other": "N/A", "data-copyright-other": "N/A", "dataset-restrictions": [ "open license - commercial use allowed" ], "data-copyright": [ "open license - commercial use allowed" ] }, "limitations": { "data-technical-limitations": "No", "data-unsuited-applications": "Model may not handle unknown values in the dialog", "data-discouraged-use": "Responses can be diverse, which is not captured by BLEU" } }, "results": { "results": { "other-metrics-definitions": "N/A", "has-previous-results": "yes", "current-evaluation": "Inform rate: how many entities in the gold response appear in the generated response.", "previous-results": "BLEU on MultiWOZ dataset.", "metrics": [ "BLEU" ], "model-abilities": "Dialog understanding, dialog policy learning", "original-evaluation": "BLEU evaluates the generation quality." } }, "curation": { "original": { "is-aggregated": "no", "aggregated-sources": "N/A", "communicative": "Generate a response according to the dialog context and database search results.", "rationale": "Gather human-to-human dialog in Chinese." }, "language": { "found": [], "crowdsourced": [ "Participatory experiment" ], "created": "N/A", "machine-generated": "N/A", "validated": "validated by data curator", "is-filtered": "not filtered", "filtered-criteria": "N/A", "obtained": [ "Crowdsourced" ], "producers-description": "An usr/sys ID indicates the creator of different data points.", "topics": "domains: attraction, hotel, restaurant, metro, taxi", "pre-processed": "N/A" }, "annotations": { "origin": "none", "rater-number": "N/A", "rater-qualifications": "N/A", "rater-training-num": "N/A", "rater-test-num": "N/A", "rater-annotation-service-bool": "no", "rater-annotation-service": [], "values": "N/A", "quality-control": [], "quality-control-details": "N/A" }, "consent": { "has-consent": "yes", "consent-policy": "Annotators agree using the dataset for research purpose.", "consent-other": "Any", "no-consent-justification": "N/A" }, "pii": { "has-pii": "unlikely", "no-pii-justification": "N/A", "is-pii-identified": "no identification", "pii-identified-method": "N/A", "is-pii-replaced": "N/A", "pii-replaced-method": "N/A", "pii-categories": [ "generic PII" ] }, "maintenance": { "has-maintenance": "no", "description": "N/A", "contact": "N/A", "contestation-mechanism": "N/A", "contestation-link": "N/A", "contestation-description": "N/A" } }, "gem": { "rationale": { "sole-task-dataset": "yes", "distinction-description": "The corpus contains rich annotation of dialogue states and dialogue acts at both user and system sides, which can be used in a wide range of tasks.", "contribution": "CrossWOZ is the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset.", "sole-language-task-dataset": "no", "model-ability": "Dialog understanding, dialog policy learning" }, "curation": { "has-additional-curation": "yes", "modification-types": [ "other" ], "modification-description": "To adapt to hugging face Datasets, we 1) separate user annotators' ID and system annotations' ID; 2) we convert the data type in goal/user state to string.", "has-additional-splits": "no", "additional-splits-description": "N/A", "additional-splits-capacicites": "N/A" }, "starting": { "research-pointers": "https://github.com/thu-coai/Convlab-2", "technical-terms": "According to the type of user goal, we group the dialogues in the training set into five categories:\n- S: 417 dialogues have only one sub-goal in HAR domains.\n- M: 1573 dialogues have multiple sub-goals (2-3) in HAR domains. However, these sub-goals do not have cross-domain informable slots.\n- M+T: 691 dialogues have multiple sub-goals in HAR domains and at least one sub-goal in the metro or taxi domain (3-5 sub-goals). The sub-goals in HAR domains do not have cross-domain informable slots.\n- CM: 1,759 dialogues have multiple sub-goals (2-5) in HAR domains with cross-domain informable slots.\n- CM+T: 572 dialogues have multiple sub-goals in HAR domains with cross-domain informable slots and at least one sub-goal in the metro or taxi domain (3-5 sub-goals).\n" } } }