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--- |
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license: cc-by-sa-4.0 |
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task_categories: |
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- text-generation |
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- text-classification |
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language: |
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- ja |
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pretty_name: Japanese Multi-domain Wizard-of-Oz |
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size_categories: |
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- 1K<n<10K |
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task_ids: |
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- dialogue-modeling |
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- parsing |
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multilinguality: |
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- monolingual |
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annotations_creators: |
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- crowdsourced |
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language_creators: |
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- crowdsourced |
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source_datasets: |
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- original |
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dataset_info: |
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features: |
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- name: dialogue_id |
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dtype: int32 |
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- name: dialogue_name |
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dtype: string |
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- name: system_name |
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dtype: string |
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- name: user_name |
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dtype: string |
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- name: goal |
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sequence: |
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- name: domain |
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dtype: string |
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- name: task |
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dtype: string |
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- name: slot |
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dtype: string |
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- name: value |
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dtype: string |
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- name: goal_description |
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sequence: |
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- name: domain |
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dtype: string |
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- name: text |
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dtype: string |
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- name: turns |
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sequence: |
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- name: turn_id |
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dtype: int32 |
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- name: speaker |
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dtype: string |
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- name: utterance |
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dtype: string |
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- name: dialogue_state |
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struct: |
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- name: belief_state |
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sequence: |
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- name: domain |
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dtype: string |
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- name: slot |
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dtype: string |
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- name: value |
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dtype: string |
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- name: book_state |
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sequence: |
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- name: domain |
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dtype: string |
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- name: slot |
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dtype: string |
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- name: value |
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dtype: string |
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- name: db_result |
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struct: |
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- name: candidate_entities |
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sequence: |
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dtype: string |
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id: entity_name |
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id: candidate_entities |
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- name: active_entity |
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sequence: |
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- name: slot |
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dtype: string |
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id: active_entity/slot |
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- name: value |
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dtype: string |
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id: active_entity/value |
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- name: book_result |
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sequence: |
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- name: domain |
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dtype: string |
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- name: success |
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dtype: string |
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- name: ref |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 60731411 |
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num_examples: 3646 |
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- name: validation |
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num_bytes: 5000420 |
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num_examples: 300 |
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- name: test |
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num_bytes: 5085276 |
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num_examples: 300 |
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download_size: 11016438 |
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dataset_size: 70817107 |
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--- |
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|
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# Dataset Card for JMultiWOZ |
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## Dataset Description |
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- **Repository:** [nu-dialouge/jmultiwoz](https://github.com/nu-dialogue/jmultiwoz) |
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- **Paper:** [JMultiWOZ: A Large-Scale Japanese Multi-Domain Task-Oriented Dialogue Dataset]() |
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- **Point of Contact:** [Atsumoto Ohashi]([email protected]) |
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### Dataset Summary |
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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. |
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### Supported Tasks |
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- **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. |
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- **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. |
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### Languages |
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The text in the dataset is in Japanese (`ja`). |
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## Dataset Usage |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("nu-dialogue/jmultiwoz", trust_remote_code=True) |
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``` |
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## Dataset Structure |
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### Data Instances |
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A data instance is a full multi-turn dialogue between a `USER` and a `SYSTEM`. Each turn has an `utterance`: |
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```json |
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[ |
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"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？", |
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"かしこまりました。ではWITH THE STYLE FUKUOKAはいかがでしょうか。" |
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] |
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``` |
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`SYSTEM` turn also has a `dialogue_state` which contains `belief_state`, `book_state`, `db_result`, and `book_result`: |
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`belief_state`: |
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```json |
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{ |
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"domain": ["general", "general", "hotel", ...], |
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"slot": ["active_domain", "city", "pricerange", ...], |
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"value": ["hotel", "福岡", "普通", ...] |
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} |
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``` |
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`book_state`: |
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```json |
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{ |
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"domain": ["hotel", "hotel", "hotel", ...], |
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"slot": ["people", "day", "stay", ...], |
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"value": [None, None, None, ...] |
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} |
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``` |
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`db_result`: |
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```json |
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{ |
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"candidate_entities": ["WITH THE STYLE FUKUOKA", "ANA クラウンプラザホテル福岡", ...], |
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"active_entity": { |
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"slot": ["city", "name", "genre", ...], |
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"value": ["福岡", "WITH THE STYLE FUKUOKA", "リゾートホテル", ...] |
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} |
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``` |
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### Data Fields |
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Each dialogue instance has the following fields: |
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- `dialogue_id` (int32): A unique identifier for the dialogue. |
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- `dialogue_name` (string): A name for the dialogue. |
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- `system_name` (string): The name of the wizard. |
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- `user_name` (string): The name of the user. |
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- `goal` (sequence): The user's goal for the dialogue. |
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- `domain` (string): The domain of the goal. |
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- `task` (string): The task of the goal. |
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- `slot` (string): The slot of the goal. |
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- `value` (string): The value of the goal. |
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- `goal_description` (sequence): A description of the user's goal. |
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- `domain` (string): The domain of the goal. |
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- `text` (string): The text of the goal. |
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- `turns` (sequence): The turns in the dialogue. |
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- `turn_id` (int32): A unique identifier for the turn. |
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- `speaker` (string): The speaker of the turn. |
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- `utterance` (string): The utterance of the turn. |
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- `dialogue_state` (struct): The dialogue state of the turn. |
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- `belief_state` (sequence): The belief state of the turn. |
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- `domain` (string): The domain of the belief state. |
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- `slot` (string): The slot of the belief state. |
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- `value` (string): The value of the belief state. |
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- `book_state` (sequence): The book state of the turn. |
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- `domain` (string): The domain of the book state. |
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- `slot` (string): The slot of the book state. |
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- `value` (string): The value of the book state. |
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- `db_result` (struct): The database result of the turn. |
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- `candidate_entities` (sequence): The candidate entities of the database result. |
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- `entity_name` (string): The name of the entity. |
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- `active_entity` (sequence): The active entity of the database result. |
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- `slot` (string): The slot of the active entity. |
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- `value` (string): The value of the active entity. |
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- `book_result` (sequence): The book result of the turn. |
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- `domain` (string): The domain of the book result. |
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- `success` (string): The success of the book result. |
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- `ref` (string): The reference of the book result. |
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### Data Splits |
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The dataset is split into a train, validation, and test split with the following sizes: |
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| | train | validation | test | |
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|--- | ---: | ---: | ---: | |
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| Number of dialogues | 3646 | 300 | 300 | |
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| Number of turns | 52,405 | 4,346 | 4,435 | |
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## Citation Information |
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```bibtex |
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@inproceedings{ohashi-etal-2024-jmultiwoz, |
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title = "JMultiWOZ: A Large-Scale Japanese Multi-Domain Task-Oriented Dialogue Dataset", |
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author = "Ohashi, Atsumoto and Hirai, Ryu and Iizuka, Shinya and Higashinaka, Ryuichiro", |
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booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation", |
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year = "2024", |
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url = "", |
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pages = "", |
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} |
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``` |
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