| # DialogZoo | |
| ## Data construction | |
| To replicate data construction, three steps are required: | |
| * Download data: ```bash scripts/download.sh``` | |
| * Convert origin data into our unified format: ```bash scripts/convert_to_unified.sh``` | |
| ``` | |
| { | |
| # Optional values: `single` or `multi`. Indicates whether it is a single-turn or multi-turn dialogue. | |
| "turn": str, | |
| # The domains involved in the dialogue (a list because some dialogues involve multiple domains). | |
| "domain": [], | |
| # The language of the dialogue, based on the original dataset annotations (e.g., en, fr, etc.). | |
| "locale": str, | |
| # The dialogue, represented as a list where each element is a dictionary for a single turn. | |
| "dialog": [ | |
| { | |
| # The roles involved in each turn. Some datasets may have multiple roles per turn, so it's a list. | |
| # For datasets without role annotations: | |
| # * Use `ROLE` for single-turn data. | |
| # * Use `ROLE1`, `ROLE2`, etc., for multi-turn data. | |
| "roles": [str, ...], | |
| # The text of the current turn. | |
| "utterance": str, | |
| # Used for the "answer" in QA tasks. | |
| "start": int, | |
| "end": int, | |
| "dialog_turn": int | |
| # Rewritten text corresponding to the current turn. | |
| "rewritten": str, | |
| # Dialogue state, represented as a list where each element includes: | |
| # Domain: Some datasets constrain slot-value pairs within specific domains. | |
| # Intent: Some datasets constrain slot-value pairs within specific intents. | |
| # Slot-value pairs: A list where each element includes a slot and its corresponding values. | |
| # Slot name: A string. | |
| # Values: A list where a slot may have multiple values. | |
| # Each value includes four parts: the value itself, the normalized value, | |
| # the character index in the current turn's text, and more. | |
| # Relation: Some slots are equal to a value, while others are greater than a value. | |
| # Defaults to "equal" if not specified. | |
| # Requested slots: A list of slots that need to be queried but are not filled in the current state. | |
| "belief_state": [ | |
| { | |
| # Intent | |
| "intent": str, | |
| # Slot-value pairs | |
| "informed_slot_value_table": [ | |
| { | |
| # Slot name | |
| "slot": str, | |
| # Values | |
| "values": [{ | |
| # Actual value | |
| "value": str, | |
| # Normalized value | |
| "cononical_value": str | |
| }, ...], | |
| # Slot-value relation | |
| "relation": str, | |
| }, | |
| ... | |
| ], | |
| # Requested slots | |
| "requested_slots": [], | |
| # Domain | |
| "domain": str, | |
| }, ... | |
| ], | |
| # Dialogue actions, represented as a list where each element includes: | |
| # Domain: Some datasets constrain slot-value pairs within specific domains. | |
| # Action: The actions involved in the current turn. | |
| # Slot-value pairs: Same as in dialogue state. | |
| "dialog_acts": [ | |
| { | |
| # Action | |
| "act": str, | |
| # Slot-value pairs | |
| "slot_value_table": [ | |
| { | |
| # Slot name | |
| "slot": str, | |
| # Slot-value relation | |
| "relation": str, | |
| # Values | |
| "values": [ | |
| { | |
| # Actual value | |
| "value": str, | |
| # Normalized value | |
| "cononical_value": str, | |
| # Start position | |
| "start": int, | |
| # End position | |
| "end": int, | |
| },... | |
| ] | |
| }, | |
| ... | |
| ], | |
| # Domain | |
| "domain": str, | |
| }, | |
| ... | |
| ], | |
| # Slot filling | |
| "slots_to_fill": { | |
| "intent": str, | |
| "slot_value_table": [ | |
| { | |
| "slot": str, | |
| "values": [ | |
| { | |
| "value": str, | |
| "start": int, | |
| "end": int | |
| } | |
| ], | |
| "relation": str, # '=', '<=', and so on | |
| } | |
| ] | |
| }, | |
| # Named entity recognition | |
| "named_entity_recognition": [ | |
| { | |
| "type": str, | |
| "values": [ | |
| { | |
| "value": str, | |
| "start": int, | |
| "end": int | |
| }, ... | |
| ] | |
| }, ... | |
| ], | |
| "characters": [ | |
| { | |
| "value": str, | |
| "start": int, | |
| "end": int | |
| } | |
| ] | |
| # Intent detection | |
| "active_intents": [str], | |
| # Query | |
| "query" { | |
| ... | |
| }, | |
| # Query result | |
| "querying_result": { | |
| ... | |
| }, | |
| # Recorded satisfied main items | |
| "main_items": [], | |
| # Aspect Sentiment Triplet Extraction task, represented as a list where each element includes three parts: | |
| # Target entity. | |
| # Related sentiment. | |
| # Words reflecting the sentiment. | |
| "aspects": [ | |
| { | |
| # Target entity | |
| "target": { | |
| # Entity value | |
| "value": str, | |
| # Start position in the current turn's text | |
| "start": int, | |
| # End position in the current turn's text | |
| "end": int | |
| }, | |
| # Category of the target entity | |
| "category": str, | |
| # Words reflecting the sentiment | |
| "opinion": { | |
| # Sentiment word | |
| "value": str, | |
| # Start position in the current turn's text | |
| "start": int, | |
| # End position in the current turn's text | |
| "end": int | |
| }, | |
| # Related sentiment | |
| "sentiment": str | |
| } | |
| ], | |
| "emotions": [ | |
| { | |
| "emotion": str, | |
| "sentiment": "positive", "negative", or "ambiguous", | |
| "evidences": [ | |
| { | |
| "turn": int, | |
| "span": str, | |
| "start": int, | |
| "end": int | |
| } | |
| ], | |
| "evidence_types": [str] | |
| } | |
| ], | |
| "kg_label": str, | |
| # Knowledge that may be required for each turn, used to select knowledge. | |
| "knowledge_to_select": str, | |
| # SQL | |
| "sql": str, | |
| # Rewritten text | |
| "rewritten": str, | |
| "roles_to_select": [str], | |
| }, | |
| ], | |
| # Summary derived from the entire dialogue. | |
| "summary": str, | |
| # Entity relations determined from the entire dialogue. | |
| "instance_relations": [ | |
| { | |
| "instance1": str, | |
| "instance2": str, | |
| "relations": [ | |
| { | |
| "relation": str, | |
| "trigger": str | |
| }, ... | |
| ] | |
| }, ... | |
| ] | |
| # Role relations determined from the entire dialogue. | |
| "role_relations": [ | |
| { | |
| "turn": int, | |
| "relation": str | |
| } | |
| ], | |
| # Used in FriendsPersona to determine a character's persona based on the entire dialogue. | |
| "role_personas": [ | |
| { | |
| "name": str, | |
| "personas": [ | |
| { | |
| "persona": str, | |
| "sentiment": int | |
| }, ... | |
| ] | |
| } | |
| ], | |
| # External knowledge required for the dialogue. | |
| "knowledge": { | |
| # `text`, `persona`, `kg`, or `schema`. | |
| "type": str, | |
| # For `text`. | |
| "value": str, | |
| # For `persona`, persona of all roles, used for personachat. | |
| "value": [ | |
| { | |
| # Role name, matching the dialogue turn. | |
| "role": str, | |
| # Persona description, which may include several sentences. | |
| "description": [] | |
| }, | |
| ... | |
| ] | |
| # For `kg`. | |
| "value": { | |
| # `directed` or `undirected`. | |
| "direction": str, | |
| # Graph. | |
| "graph": [ | |
| { | |
| # Source node. | |
| "source": str, | |
| # Target node. | |
| "target": str, | |
| # Relation. | |
| "relation": str | |
| }, | |
| ... | |
| ] | |
| } | |
| # For `schema`. | |
| "value": { | |
| ... | |
| } | |
| # For `dialogue`. | |
| "value": { | |
| "dialog": [], | |
| "relations": [] | |
| } | |
| # For `wiki`. | |
| "value": { | |
| ... | |
| } | |
| # For `sql`. | |
| "value": [ | |
| { | |
| "turn": int, | |
| "sql": str, | |
| "result": ... | |
| }, ... | |
| ], | |
| # For dialogues based on specific article excerpts, this field indicates the article and section titles. | |
| "value": { | |
| "article title": str, | |
| "section title": str | |
| }, | |
| } | |
| } | |
| ``` | |
| * Linearize: ```bash scripts/convert_to_seq.sh``` | |
| The processed data is located at ```DialogZoo.tar```. | |
| ## Data statistics | |
| |ID| MRC| ER| MCQA| QCR| RRR| CI| SF|DCRG|CC |ABSA |T2S |DST |DT |DS |SP |NLI|Total| | |
| |-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-| | |
| |34,963 | 368,490 | 135,356 | 196,620 | 33,192 | 5,037 | 36,385 | 104,100 | 390,463 | 262,876 | 17,328 | 30,220 | 298,358 | 60,563 | 27,192 | 31,279 | 169,654 | 2,202,076| |