README.md

---
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 = "",
}
```