Dataset Card for JMultiWOZ

Dataset Summary

JMultiWOZ is a large-scale Japanese multi-domain task-oriented dialogue dataset. The dataset is collected using the Wizard-of-Oz (WoZ) methodology, where two human annotators simulate the user and the system. The dataset contains 4,246 dialogues across 6 domains, including restaurant, hotel, attraction, shopping, taxi, and weather. Available annotations include user goal, dialogue state, and utterances.

Supported Tasks

• Dialogue State Tracking: The dataset can be used to train models for dialogue state tracking, which is the task of predicting the user's belief state at each turn in the dialogue.
• Dialogue Generation: The dataset can be used to train models for dialogue generation, which is the task of generating a response given the dialogue history.

Languages

The text in the dataset is in Japanese (ja).

Dataset Usage

from datasets import load_dataset

dataset = load_dataset("nu-dialogue/jmultiwoz", trust_remote_code=True)

Dataset Structure

Data Instances

A data instance is a full multi-turn dialogue between a USER and a SYSTEM. Each turn has an utterance:

[
  "福岡へ行くよていなのですが、値段が普通くらいの宿泊施設を探してもらっていいですか？",
  "かしこまりました。ではWITH THE STYLE FUKUOKAはいかがでしょうか。"
]

SYSTEM turn also has a dialogue_state which contains belief_state, book_state, db_result, and book_result:

belief_state:

{
  "domain": ["general", "general", "hotel", ...],
  "slot": ["active_domain", "city", "pricerange", ...],
  "value": ["hotel", "福岡", "普通", ...]
}

book_state:

{
  "domain": ["hotel", "hotel", "hotel", ...],
  "slot": ["people", "day", "stay", ...],
  "value": [None, None, None, ...]
}

db_result:

{
  "candidate_entities": ["WITH THE STYLE FUKUOKA", "ANA クラウンプラザホテル福岡", ...],
  "active_entity": {
    "slot": ["city", "name", "genre", ...],
    "value": ["福岡", "WITH THE STYLE FUKUOKA", "リゾートホテル", ...]
}

Data Fields

Each dialogue instance has the following fields:

• dialogue_id (int32): A unique identifier for the dialogue.
• dialogue_name (string): A name for the dialogue.
• system_name (string): The name of the wizard.
• user_name (string): The name of the user.
• goal (sequence): The user's goal for the dialogue.
  • domain (string): The domain of the goal.
  • task (string): The task of the goal.
  • slot (string): The slot of the goal.
  • value (string): The value of the goal.
• goal_description (sequence): A description of the user's goal.
  • domain (string): The domain of the goal.
  • text (string): The text of the goal.
• turns (sequence): The turns in the dialogue.
  • turn_id (int32): A unique identifier for the turn.
  • speaker (string): The speaker of the turn.
  • utterance (string): The utterance of the turn.
  • dialogue_state (struct): The dialogue state of the turn.
    • belief_state (sequence): The belief state of the turn.
      • domain (string): The domain of the belief state.
      • slot (string): The slot of the belief state.
      • value (string): The value of the belief state.
    • book_state (sequence): The book state of the turn.
      • domain (string): The domain of the book state.
      • slot (string): The slot of the book state.
      • value (string): The value of the book state.
    • db_result (struct): The database result of the turn.
      • candidate_entities (sequence): The candidate entities of the database result.
        • entity_name (string): The name of the entity.
      • active_entity (sequence): The active entity of the database result.
        • slot (string): The slot of the active entity.
        • value (string): The value of the active entity.
    • book_result (sequence): The book result of the turn.
      • domain (string): The domain of the book result.
      • success (string): The success of the book result.
      • ref (string): The reference of the book result.

Data Splits

The dataset is split into a train, validation, and test split with the following sizes:

	train	validation	test
Number of dialogues	3646	300	300
Number of turns	52,405	4,346	4,435

Citation Information

@inproceedings{ohashi-etal-2024-jmultiwoz,
    title = "JMultiWOZ: A Large-Scale Japanese Multi-Domain Task-Oriented Dialogue Dataset",
    author = "Ohashi, Atsumoto and Hirai, Ryu and Iizuka, Shinya and Higashinaka, Ryuichiro",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation",
    year = "2024",
    url = "",
    pages = "",
}