add data card in json format

CrossWOZ_data_card.json

@@ -1 +1,179 @@
-{}
+{
+  "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     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'',\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}",
+      "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"
+    }
+  }
+}