| --- |
| license: cc-by-sa-4.0 |
| task_categories: |
| - text-generation |
| - text-classification |
| language: |
| - ja |
| pretty_name: Japanese Multi-domain Wizard-of-Oz |
| size_categories: |
| - 1K<n<10K |
| task_ids: |
| - dialogue-modeling |
| - parsing |
| multilinguality: |
| - monolingual |
| annotations_creators: |
| - crowdsourced |
| language_creators: |
| - crowdsourced |
| source_datasets: |
| - original |
| dataset_info: |
| features: |
| - name: dialogue_id |
| dtype: int32 |
| - name: dialogue_name |
| dtype: string |
| - name: system_name |
| dtype: string |
| - name: user_name |
| dtype: string |
| - name: goal |
| sequence: |
| - name: domain |
| dtype: string |
| - name: task |
| dtype: string |
| - name: slot |
| dtype: string |
| - name: value |
| dtype: string |
| - name: goal_description |
| sequence: |
| - name: domain |
| dtype: string |
| - name: text |
| dtype: string |
| - name: turns |
| sequence: |
| - name: turn_id |
| dtype: int32 |
| - name: speaker |
| dtype: string |
| - name: utterance |
| dtype: string |
| - name: dialogue_state |
| struct: |
| - name: belief_state |
| sequence: |
| - name: domain |
| dtype: string |
| - name: slot |
| dtype: string |
| - name: value |
| dtype: string |
| - name: book_state |
| sequence: |
| - name: domain |
| dtype: string |
| - name: slot |
| dtype: string |
| - name: value |
| dtype: string |
| - name: db_result |
| struct: |
| - name: candidate_entities |
| sequence: |
| dtype: string |
| id: entity_name |
| id: candidate_entities |
| - name: active_entity |
| sequence: |
| - name: slot |
| dtype: string |
| id: active_entity/slot |
| - name: value |
| dtype: string |
| id: active_entity/value |
| - name: book_result |
| sequence: |
| - name: domain |
| dtype: string |
| - name: success |
| dtype: string |
| - name: ref |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 60731411 |
| num_examples: 3646 |
| - name: validation |
| num_bytes: 5000420 |
| num_examples: 300 |
| - name: test |
| num_bytes: 5085276 |
| num_examples: 300 |
| download_size: 11016438 |
| dataset_size: 70817107 |
| --- |
| |
| # Dataset Card for JMultiWOZ |
|
|
| ## Dataset Description |
|
|
| - **Repository:** [nu-dialouge/jmultiwoz](https://github.com/nu-dialogue/jmultiwoz) |
| - **Paper:** [JMultiWOZ: A Large-Scale Japanese Multi-Domain Task-Oriented Dialogue Dataset]() |
| - **Point of Contact:** [Atsumoto Ohashi](ohashi.atsumoto.c0@s.mail.nagoya-u.ac.jp) |
|
|
| ### 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 |
| ```python |
| 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`: |
| ```json |
| [ |
| "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`: |
| ```json |
| { |
| "domain": ["general", "general", "hotel", ...], |
| "slot": ["active_domain", "city", "pricerange", ...], |
| "value": ["hotel", "福岡", "普通", ...] |
| } |
| ``` |
|
|
| `book_state`: |
| ```json |
| { |
| "domain": ["hotel", "hotel", "hotel", ...], |
| "slot": ["people", "day", "stay", ...], |
| "value": [None, None, None, ...] |
| } |
| ``` |
|
|
| `db_result`: |
| ```json |
| { |
| "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 |
| ```bibtex |
| @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 = "", |
| } |
| ``` |
|
|
