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Datasets:
GEM
/
CrossWOZ

Languages:
Chinese
Multilinguality:
unknown
Size Categories:
unknown
Language Creators:
unknown
Annotations Creators:
none
Source Datasets:
original
Tags:
dialog-response-generation
License:
Dataset card Files Community
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add data card in json format

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  1. CrossWOZ_data_card.json +179 -1
CrossWOZ_data_card.json CHANGED
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- {}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "overview": {
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+ "where": {
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+ "has-leaderboard": "no",
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+ "leaderboard-url": "N/A",
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+ "leaderboard-description": "N/A",
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+ "website": "https://github.com/thu-coai/CrossWOZ",
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+ "data-url": "https://github.com/thu-coai/CrossWOZ",
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+ "paper-url": "https://aclanthology.org/2020.tacl-1.19.pdf",
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+ "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}",
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+ "contact-name": "Qi Zhu",
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+ "contact-email": "zhuq96@gmail.com"
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+ },
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+ "languages": {
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+ "is-multilingual": "no",
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+ "license": "apache-2.0: Apache License 2.0",
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+ "task-other": "N/A",
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+ "language-names": [
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+ "Chinese"
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+ ],
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+ "license-other": "N/A",
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+ "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.",
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+ "task": "Dialog Response Generation",
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+ "communicative": "Generate a response according to the dialog context and database search results."
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+ },
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+ "credit": {
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+ "organization-type": [
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+ "academic"
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+ ],
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+ "organization-names": "Tsinghua University",
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+ "creators": "Qi Zhu, Kaili Huang, Zheng Zhang, Xiaoyan Zhu, and Minlie Huang from CoAI group, Tsinghua University",
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+ "funding": "National Science Foundation of China, National Key R&D Program of China ",
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+ "gem-added-by": "Qi Zhu (Tsinghua University)"
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+ },
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+ "structure": {
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+ "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\".",
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+ "structure-description": "",
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+ "structure-labels": "",
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+ "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 |",
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+ "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': '',\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': [],\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 {'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 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'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': '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}",
41
+ "structure-splits-criteria": "",
42
+ "structure-outlier": ""
43
+ }
44
+ },
45
+ "context": {
46
+ "previous": {
47
+ "is-deployed": "no",
48
+ "described-risks": "N/A",
49
+ "changes-from-observation": "N/A"
50
+ },
51
+ "underserved": {
52
+ "helps-underserved": "yes",
53
+ "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."
54
+ },
55
+ "biases": {
56
+ "has-biases": "no",
57
+ "bias-analyses": "N/A",
58
+ "speaker-distibution": "Yes"
59
+ }
60
+ },
61
+ "considerations": {
62
+ "pii": {
63
+ "risks-description": "No"
64
+ },
65
+ "licenses": {
66
+ "dataset-restrictions-other": "N/A",
67
+ "data-copyright-other": "N/A",
68
+ "dataset-restrictions": [
69
+ "open license - commercial use allowed"
70
+ ],
71
+ "data-copyright": [
72
+ "open license - commercial use allowed"
73
+ ]
74
+ },
75
+ "limitations": {
76
+ "data-technical-limitations": "No",
77
+ "data-unsuited-applications": "Model may not handle unknown values in the dialog",
78
+ "data-discouraged-use": "Responses can be diverse, which is not captured by BLEU"
79
+ }
80
+ },
81
+ "results": {
82
+ "results": {
83
+ "other-metrics-definitions": "N/A",
84
+ "has-previous-results": "yes",
85
+ "current-evaluation": "Inform rate: how many entities in the gold response appear in the generated response.",
86
+ "previous-results": "BLEU on MultiWOZ dataset.",
87
+ "metrics": [
88
+ "BLEU"
89
+ ],
90
+ "model-abilities": "Dialog understanding, dialog policy learning",
91
+ "original-evaluation": "BLEU evaluates the generation quality."
92
+ }
93
+ },
94
+ "curation": {
95
+ "original": {
96
+ "is-aggregated": "no",
97
+ "aggregated-sources": "N/A",
98
+ "communicative": "Generate a response according to the dialog context and database search results.",
99
+ "rationale": "Gather human-to-human dialog in Chinese."
100
+ },
101
+ "language": {
102
+ "found": [],
103
+ "crowdsourced": [
104
+ "Participatory experiment"
105
+ ],
106
+ "created": "N/A",
107
+ "machine-generated": "N/A",
108
+ "validated": "validated by data curator",
109
+ "is-filtered": "not filtered",
110
+ "filtered-criteria": "N/A",
111
+ "obtained": [
112
+ "Crowdsourced"
113
+ ],
114
+ "producers-description": "An usr/sys ID indicates the creator of different data points.",
115
+ "topics": "domains: attraction, hotel, restaurant, metro, taxi",
116
+ "pre-processed": "N/A"
117
+ },
118
+ "annotations": {
119
+ "origin": "none",
120
+ "rater-number": "N/A",
121
+ "rater-qualifications": "N/A",
122
+ "rater-training-num": "N/A",
123
+ "rater-test-num": "N/A",
124
+ "rater-annotation-service-bool": "no",
125
+ "rater-annotation-service": [],
126
+ "values": "N/A",
127
+ "quality-control": [],
128
+ "quality-control-details": "N/A"
129
+ },
130
+ "consent": {
131
+ "has-consent": "yes",
132
+ "consent-policy": "Annotators agree using the dataset for research purpose.",
133
+ "consent-other": "Any",
134
+ "no-consent-justification": "N/A"
135
+ },
136
+ "pii": {
137
+ "has-pii": "unlikely",
138
+ "no-pii-justification": "N/A",
139
+ "is-pii-identified": "no identification",
140
+ "pii-identified-method": "N/A",
141
+ "is-pii-replaced": "N/A",
142
+ "pii-replaced-method": "N/A",
143
+ "pii-categories": [
144
+ "generic PII"
145
+ ]
146
+ },
147
+ "maintenance": {
148
+ "has-maintenance": "no",
149
+ "description": "N/A",
150
+ "contact": "N/A",
151
+ "contestation-mechanism": "N/A",
152
+ "contestation-link": "N/A",
153
+ "contestation-description": "N/A"
154
+ }
155
+ },
156
+ "gem": {
157
+ "rationale": {
158
+ "sole-task-dataset": "yes",
159
+ "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.",
160
+ "contribution": "CrossWOZ is the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset.",
161
+ "sole-language-task-dataset": "no",
162
+ "model-ability": "Dialog understanding, dialog policy learning"
163
+ },
164
+ "curation": {
165
+ "has-additional-curation": "yes",
166
+ "modification-types": [
167
+ "other"
168
+ ],
169
+ "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.",
170
+ "has-additional-splits": "no",
171
+ "additional-splits-description": "N/A",
172
+ "additional-splits-capacicites": "N/A"
173
+ },
174
+ "starting": {
175
+ "research-pointers": "https://github.com/thu-coai/Convlab-2",
176
+ "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"
177
+ }
178
+ }
179
+ }