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Sebastian Gehrmann commited on
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38c9ec5
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  1. schema_guided_dialog.json +9 -6
schema_guided_dialog.json CHANGED
@@ -5,9 +5,9 @@
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  "leaderboard-url": "N/A",
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  "leaderboard-description": "N/A",
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  "website": "n/a",
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- "data-url": "https://github.com/google-research-datasets/dstc8-schema-guided-dialogue",
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- "paper-url": "https://arxiv.org/abs/1909.05855",
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- "paper-bibtext": "{\n@inproceedings{rastogi2020towards,\n title={Towards scalable multi-domain conversational agents: The schema-guided dialogue dataset},\n author={Rastogi, Abhinav and Zang, Xiaoxue and Sunkara, Srinivas and Gupta, Raghav and Khaitan, Pranav},\n booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},\n volume={34},\n number={05},\n pages={8689--8696},\n year={2020}\n}",
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  "contact-email": "[email protected]",
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  "contact-name": "Abhinav Rastogi"
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  },
@@ -35,13 +35,16 @@
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  "gem-added-by": "Wanyu Du wrote the initial data card and Yacine Jernite the data loader. Simon Mille updated the data card with the additional splits. Sebastian Gehrmann migrated the data card and loader to the v2 version and extended the missing information."
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  },
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  "structure": {
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- "data-fields": "Each dialog instance has the following fields:\n* `dialogue_id`: A unique identifier for a dialogue.\n* `services`: A list of services present in the dialogue.\n* `turns`: A list of annotated system or user utterances. Each turn consists of the following fields:\n\t* `speaker`: The speaker for the turn, either `USER` or `SYSTEM`.\n\t* `utterance`: A string containing the natural language utterance.\n\t* `frames`: A list of frames, each frame containing annotations for a single service and consists of the following fields:\n\t\t* `service`: The name of the service corresponding to the frame. The slots and intents used in the following fields are taken from the schema of this service.\n\t\t* `slots`: A list of slot spans in the utterance, only provided for non-categorical slots. Each slot span contains the following fields:\n\t\t\t* `slot`: The name of the slot.\n\t\t\t* `start`: The index of the starting character in the utterance corresponding to the slot value.\n\t\t\t* `exclusive_end`: The index of the character just after the last character corresponding to the slot value in the utterance.\n\t\t* `actions`: A list of actions corresponding to the system. Each action has the following fields:\n\t\t\t* `act`: The type of action.\n\t\t\t* `slot`: (optional) A slot argument for some of the actions.\n\t\t\t* `values`: (optional) A list of values assigned to the slot. If the values list is non-empty, then the slot must be present.\n\t\t\t* `canonical_values`: (optional) The values in their canonicalized form as used by the service. It is a list of strings of the same length as values.\n\t\t* `service_call`: (system turns only, optional) The request sent to the service. It consists of the following fields:\n\t\t\t* `method`: The name of the intent or function of the service or API being executed.\n\t\t\t* `parameters`: A pair of lists of the same lengths: `parameter_slot_name` contains slot names and `parameter_canonical_value` contains the corresponding values in their canonicalized form.\n\t\t* `service_results`: (system turns only, optional) A list of entities containing the results obtained from the service. It is only available for turns in which a service call is made. Each entity is represented as a pair of lists of the same length: `service_slot_name` contains slot names and `service_canonical_value` contains the corresponding canonical values.\n\t\t* `state`: (user turns only) The dialogue state corresponding to the service. It consists of the following fields:\n\t\t\t* `active_intent`: The intent corresponding to the service of the frame which is currently being fulfilled by the system. It takes the value \"NONE\" if none of the intents are active.\n\t\t\t* `requested_slots`: A list of slots requested by the user in the current turn.\n\t\t\t* `slot_values`: A pair of lists of the same lengths: `slot_name` contains slot names and `slot_value_list` contains the corresponding lists of strings. For categorical slots, this list contains a single value assigned to the slot. For non-categorical slots, all the values in this list are spoken variations of each other and are equivalent (e.g, \"6 pm\", \"six in the evening\", \"evening at 6\" etc.).\n\n",
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  "structure-description": "n/a",
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  "structure-labels": "n/a",
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- "structure-example": "{'dialogue_id': '1_00000',\n 'services': ['Restaurants_1'],\n 'turns':\n {'frames':\n \t[{'actions': [{'act': [6],\n 'canonical_values': [['FindRestaurants']],\n 'slot': ['intent'],\n 'values': [['FindRestaurants']]}],\n 'service': ['Restaurants_1'],\n 'service_call': [{'method': '',\n 'parameters': {'parameter_canonical_value': [],\n 'parameter_slot_name': []}}],\n 'service_results': [{'service_results_list': []}],\n 'slots': [{'exclusive_end': [], 'slot': [], 'start': []}],\n 'state': [{'active_intent': 'FindRestaurants',\n \t\t\t 'requested_slots': [],\n \t\t\t 'slot_values': {'slot_name': [], 'slot_value_list': []}}]},\n {'actions': [{'act': [13],\n 'canonical_values': [[]],\n 'slot': ['city'],\n 'values': [[]]}],\n 'service': ['Restaurants_1'],\n 'service_call': [{'method': '',\n 'parameters': {'parameter_canonical_value': [],\n 'parameter_slot_name': []}}],\n 'service_results': [{'service_results_list': []}],\n 'slots': [{'exclusive_end': [], 'slot': [], 'start': []}],\n 'state': [{'active_intent': '',\n \t\t 'requested_slots': [],\n \t\t 'slot_values': {'slot_name': [], 'slot_value_list': []}}]},\n ...,]}\n 'speaker': [0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1],\n 'utterance': [\n 'I am feeling hungry so I would like to find a place to eat.',\n 'Do you have a specific which you want the eating place to be located at?',\n 'I would like for it to be in San Jose.',\n 'Is there a specific cuisine type you enjoy, such as Mexican, Italian or something else?',\n 'I usually like eating the American type of food.',\n 'I see that at 71 Saint Peter there is a good restaurant which is in San Jose.',\n 'Can you give me the address of this restaurant.',\n 'If you want to go to this restaurant you can find it at 71 North San Pedro Street.',\n 'Can you give me the phone number that I can contact them with?',\n 'If you want to phone them you can at 408-971-8523.',\n 'Is there some other restaurant which you can suggest?',\n 'How would you like Bazille restaurant which is situated in San Jose.',\n 'Do you have another restaurant matching my needs? For example a restaurant which is economical and is located in Palo Alto.',\n 'I see that 7 restaurants suit to what you requested. Bird Dog seems as a good restaurant and is located in Palo Alto.',\n 'Alright, that seems good. I would like to make a booking at this restaurant.',\n 'For which time do you want the booking to be?',\n 'I will be eating there at 11:30 am so make it for then.',\n 'Can you please confirm that you want to book a table for 2 at 11:30 am at the Bird Dog restaurant in Palo Alto for today.',\n 'That suits me well. Can you tell me if they feature live music?',\n 'Your booking has been made without errors, but unfortunately they do not have live music.',\n 'Will I be able to find liquor there? Can you give me the address of their location?',\n 'The restaurant is located at 420 Ramona Street. Unfortunately they do not serve alcohol at the restaurant.',\n 'I appreciate it very much. That would be all.',\n 'Have a good time!'\n ]}",
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  "structure-splits": "The dataset is split into a train, validation, and test set with the following sizes:\n\n| | Train | Validation | Test |\n| --- | --- | --- | --- |\n| \\# of dialogues | 16142 | 2482 | 4201 |\n| \\# of turns | 48426 | 7446 | 12603 |",
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  "structure-splits-criteria": "The data is generally split i.i.d, but some topics only appear in training and some only for testing. For example, the domains Messaging, Payment, and Train are test-only. ",
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  "structure-outlier": "n/a"
 
 
 
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  }
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  },
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  "curation": {
@@ -55,7 +58,7 @@
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  "found": [],
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  "crowdsourced": [],
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  "created": "N/A",
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- "machine-generated": "https://github.com/google-research-datasets/dstc8-schema-guided-dialogue",
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  "validated": "not validated",
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  "is-filtered": "not filtered",
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  "filtered-criteria": "N/A",
 
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  "leaderboard-url": "N/A",
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  "leaderboard-description": "N/A",
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  "website": "n/a",
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+ "data-url": "[Github[(https://github.com/google-research-datasets/dstc8-schema-guided-dialogue)",
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+ "paper-url": "[Arxiv](https://arxiv.org/abs/1909.05855)",
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+ "paper-bibtext": "```\n{\n@inproceedings{rastogi2020towards,\n title={Towards scalable multi-domain conversational agents: The schema-guided dialogue dataset},\n author={Rastogi, Abhinav and Zang, Xiaoxue and Sunkara, Srinivas and Gupta, Raghav and Khaitan, Pranav},\n booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},\n volume={34},\n number={05},\n pages={8689--8696},\n year={2020}\n}\n```",
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  "contact-email": "[email protected]",
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  "contact-name": "Abhinav Rastogi"
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  },
 
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  "gem-added-by": "Wanyu Du wrote the initial data card and Yacine Jernite the data loader. Simon Mille updated the data card with the additional splits. Sebastian Gehrmann migrated the data card and loader to the v2 version and extended the missing information."
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  },
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  "structure": {
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+ "data-fields": "Each dialog instance has the following fields:\n\n* `dialogue_id`: A unique identifier for a dialogue.\n* `services`: A list of services present in the dialogue.\n* `turns`: A list of annotated system or user utterances. Each turn consists of the following fields:\n\t* `speaker`: The speaker for the turn, either `USER` or `SYSTEM`.\n\t* `utterance`: A string containing the natural language utterance.\n\t* `frames`: A list of frames, each frame containing annotations for a single service and consists of the following fields:\n\t\t* `service`: The name of the service corresponding to the frame. The slots and intents used in the following fields are taken from the schema of this service.\n\t\t* `slots`: A list of slot spans in the utterance, only provided for non-categorical slots. Each slot span contains the following fields:\n\t\t\t* `slot`: The name of the slot.\n\t\t\t* `start`: The index of the starting character in the utterance corresponding to the slot value.\n\t\t\t* `exclusive_end`: The index of the character just after the last character corresponding to the slot value in the utterance.\n\t\t* `actions`: A list of actions corresponding to the system. Each action has the following fields:\n\t\t\t* `act`: The type of action.\n\t\t\t* `slot`: (optional) A slot argument for some of the actions.\n\t\t\t* `values`: (optional) A list of values assigned to the slot. If the values list is non-empty, then the slot must be present.\n\t\t\t* `canonical_values`: (optional) The values in their canonicalized form as used by the service. It is a list of strings of the same length as values.\n\t\t* `service_call`: (system turns only, optional) The request sent to the service. It consists of the following fields:\n\t\t\t* `method`: The name of the intent or function of the service or API being executed.\n\t\t\t* `parameters`: A pair of lists of the same lengths: `parameter_slot_name` contains slot names and `parameter_canonical_value` contains the corresponding values in their canonicalized form.\n\t\t* `service_results`: (system turns only, optional) A list of entities containing the results obtained from the service. It is only available for turns in which a service call is made. Each entity is represented as a pair of lists of the same length: `service_slot_name` contains slot names and `service_canonical_value` contains the corresponding canonical values.\n\t\t* `state`: (user turns only) The dialogue state corresponding to the service. It consists of the following fields:\n\t\t\t* `active_intent`: The intent corresponding to the service of the frame which is currently being fulfilled by the system. It takes the value \"NONE\" if none of the intents are active.\n\t\t\t* `requested_slots`: A list of slots requested by the user in the current turn.\n\t\t\t* `slot_values`: A pair of lists of the same lengths: `slot_name` contains slot names and `slot_value_list` contains the corresponding lists of strings. For categorical slots, this list contains a single value assigned to the slot. For non-categorical slots, all the values in this list are spoken variations of each other and are equivalent (e.g, \"6 pm\", \"six in the evening\", \"evening at 6\" etc.).\n\n",
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  "structure-description": "n/a",
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  "structure-labels": "n/a",
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+ "structure-example": "```\n{'dialogue_id': '1_00000',\n 'services': ['Restaurants_1'],\n 'turns':\n {'frames':\n \t[{'actions': [{'act': [6],\n 'canonical_values': [['FindRestaurants']],\n 'slot': ['intent'],\n 'values': [['FindRestaurants']]}],\n 'service': ['Restaurants_1'],\n 'service_call': [{'method': '',\n 'parameters': {'parameter_canonical_value': [],\n 'parameter_slot_name': []}}],\n 'service_results': [{'service_results_list': []}],\n 'slots': [{'exclusive_end': [], 'slot': [], 'start': []}],\n 'state': [{'active_intent': 'FindRestaurants',\n \t\t\t 'requested_slots': [],\n \t\t\t 'slot_values': {'slot_name': [], 'slot_value_list': []}}]},\n {'actions': [{'act': [13],\n 'canonical_values': [[]],\n 'slot': ['city'],\n 'values': [[]]}],\n 'service': ['Restaurants_1'],\n 'service_call': [{'method': '',\n 'parameters': {'parameter_canonical_value': [],\n 'parameter_slot_name': []}}],\n 'service_results': [{'service_results_list': []}],\n 'slots': [{'exclusive_end': [], 'slot': [], 'start': []}],\n 'state': [{'active_intent': '',\n \t\t 'requested_slots': [],\n \t\t 'slot_values': {'slot_name': [], 'slot_value_list': []}}]},\n ...,]}\n 'speaker': [0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1],\n 'utterance': [\n 'I am feeling hungry so I would like to find a place to eat.',\n 'Do you have a specific which you want the eating place to be located at?',\n 'I would like for it to be in San Jose.',\n 'Is there a specific cuisine type you enjoy, such as Mexican, Italian or something else?',\n 'I usually like eating the American type of food.',\n 'I see that at 71 Saint Peter there is a good restaurant which is in San Jose.',\n 'Can you give me the address of this restaurant.',\n 'If you want to go to this restaurant you can find it at 71 North San Pedro Street.',\n 'Can you give me the phone number that I can contact them with?',\n 'If you want to phone them you can at 408-971-8523.',\n 'Is there some other restaurant which you can suggest?',\n 'How would you like Bazille restaurant which is situated in San Jose.',\n 'Do you have another restaurant matching my needs? For example a restaurant which is economical and is located in Palo Alto.',\n 'I see that 7 restaurants suit to what you requested. Bird Dog seems as a good restaurant and is located in Palo Alto.',\n 'Alright, that seems good. I would like to make a booking at this restaurant.',\n 'For which time do you want the booking to be?',\n 'I will be eating there at 11:30 am so make it for then.',\n 'Can you please confirm that you want to book a table for 2 at 11:30 am at the Bird Dog restaurant in Palo Alto for today.',\n 'That suits me well. Can you tell me if they feature live music?',\n 'Your booking has been made without errors, but unfortunately they do not have live music.',\n 'Will I be able to find liquor there? Can you give me the address of their location?',\n 'The restaurant is located at 420 Ramona Street. Unfortunately they do not serve alcohol at the restaurant.',\n 'I appreciate it very much. That would be all.',\n 'Have a good time!'\n ]}\n```",
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  "structure-splits": "The dataset is split into a train, validation, and test set with the following sizes:\n\n| | Train | Validation | Test |\n| --- | --- | --- | --- |\n| \\# of dialogues | 16142 | 2482 | 4201 |\n| \\# of turns | 48426 | 7446 | 12603 |",
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  "structure-splits-criteria": "The data is generally split i.i.d, but some topics only appear in training and some only for testing. For example, the domains Messaging, Payment, and Train are test-only. ",
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  "structure-outlier": "n/a"
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+ },
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+ "what": {
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+ "dataset": "The GEM version of this dataset functions as a response generation dataset. The input specifies dialog acts that a model needs to verbalize. The Schema-Guided Dialog dataset is challenging since it comprises multiple domains from hotel and travel to restaurants, and a wide range of dialog acts. The context of each conversation is provided as well. "
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  }
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  },
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  "curation": {
 
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  "found": [],
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  "crowdsourced": [],
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  "created": "N/A",
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+ "machine-generated": "[Github](https://github.com/google-research-datasets/dstc8-schema-guided-dialogue)",
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  "validated": "not validated",
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  "is-filtered": "not filtered",
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  "filtered-criteria": "N/A",