| --- |
| annotations_creators: |
| - crowdsourced |
| language_creators: |
| - crowdsourced |
| language: |
| - en |
| license: |
| - cc-by-4.0 |
| multilinguality: |
| - monolingual |
| size_categories: |
| - 10K<n<100K |
| source_datasets: |
| - original |
| task_categories: |
| - text-generation |
| - fill-mask |
| task_ids: |
| - dialogue-modeling |
| paperswithcode_id: null |
| pretty_name: taskmaster3 |
| dataset_info: |
| features: |
| - name: conversation_id |
| dtype: string |
| - name: vertical |
| dtype: string |
| - name: instructions |
| dtype: string |
| - name: scenario |
| dtype: string |
| - name: utterances |
| list: |
| - name: index |
| dtype: int32 |
| - name: speaker |
| dtype: string |
| - name: text |
| dtype: string |
| - name: apis |
| list: |
| - name: name |
| dtype: string |
| - name: index |
| dtype: int32 |
| - name: args |
| list: |
| - name: arg_name |
| dtype: string |
| - name: arg_value |
| dtype: string |
| - name: response |
| list: |
| - name: response_name |
| dtype: string |
| - name: response_value |
| dtype: string |
| - name: segments |
| list: |
| - name: start_index |
| dtype: int32 |
| - name: end_index |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: annotations |
| list: |
| - name: name |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 143609327 |
| num_examples: 23757 |
| download_size: 313402141 |
| dataset_size: 143609327 |
| --- |
| |
| # Dataset Card for taskmaster3 |
|
|
| ## Table of Contents |
| - [Dataset Description](#dataset-description) |
| - [Dataset Summary](#dataset-summary) |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
| - [Languages](#languages) |
| - [Dataset Structure](#dataset-structure) |
| - [Data Instances](#data-instances) |
| - [Data Fields](#data-fields) |
| - [Data Splits](#data-splits) |
| - [Dataset Creation](#dataset-creation) |
| - [Curation Rationale](#curation-rationale) |
| - [Source Data](#source-data) |
| - [Annotations](#annotations) |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) |
| - [Considerations for Using the Data](#considerations-for-using-the-data) |
| - [Social Impact of Dataset](#social-impact-of-dataset) |
| - [Discussion of Biases](#discussion-of-biases) |
| - [Other Known Limitations](#other-known-limitations) |
| - [Additional Information](#additional-information) |
| - [Dataset Curators](#dataset-curators) |
| - [Licensing Information](#licensing-information) |
| - [Citation Information](#citation-information) |
| - [Contributions](#contributions) |
|
|
| ## Dataset Description |
|
|
| - **Homepage:** [Taskmaster](https://research.google/tools/datasets/taskmaster-1/) |
| - **Repository:** [GitHub](https://github.com/google-research-datasets/Taskmaster/tree/master/TM-3-2020) |
| - **Paper:** [Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset](https://arxiv.org/abs/1909.05358) |
| - **Leaderboard:** N/A |
| - **Point of Contact:** [Taskmaster Googlegroup](taskmaster-datasets@googlegroups.com) |
|
|
| ### Dataset Summary |
|
|
| Taskmaster is dataset for goal oriented conversations. The Taskmaster-3 dataset consists of 23,757 movie ticketing dialogs. |
| By "movie ticketing" we mean conversations where the customer's goal is to purchase tickets after deciding |
| on theater, time, movie name, number of tickets, and date, or opt out of the transaction. This collection |
| was created using the "self-dialog" method. This means a single, crowd-sourced worker is |
| paid to create a conversation writing turns for both speakers, i.e. the customer and the ticketing agent. |
|
|
| ### Supported Tasks and Leaderboards |
|
|
| [More Information Needed] |
|
|
| ### Languages |
|
|
| The dataset is in English language. |
|
|
| ## Dataset Structure |
|
|
| ### Data Instances |
|
|
| A typical example looks like this |
|
|
| ``` |
| { |
| "conversation_id": "dlg-ddee80da-9ffa-4773-9ce7-f73f727cb79c", |
| "instructions": "SCENARIO: Pretend you’re *using a digital assistant to purchase tickets for a movie currently showing in theaters*. ...", |
| "scenario": "4 exchanges with 1 error and predefined variables", |
| "utterances": [ |
| { |
| "apis": [], |
| "index": 0, |
| "segments": [ |
| { |
| "annotations": [ |
| { |
| "name": "num.tickets" |
| } |
| ], |
| "end_index": 21, |
| "start_index": 20, |
| "text": "2" |
| }, |
| { |
| "annotations": [ |
| { |
| "name": "name.movie" |
| } |
| ], |
| "end_index": 42, |
| "start_index": 37, |
| "text": "Mulan" |
| } |
| ], |
| "speaker": "user", |
| "text": "I would like to buy 2 tickets to see Mulan." |
| }, |
| { |
| "index": 6, |
| "segments": [], |
| "speaker": "user", |
| "text": "Yes.", |
| "apis": [ |
| { |
| "args": [ |
| { |
| "arg_name": "name.movie", |
| "arg_value": "Mulan" |
| }, |
| { |
| "arg_name": "name.theater", |
| "arg_value": "Mountain AMC 16" |
| } |
| ], |
| "index": 6, |
| "name": "book_tickets", |
| "response": [ |
| { |
| "response_name": "status", |
| "response_value": "success" |
| } |
| ] |
| } |
| ] |
| } |
| ], |
| "vertical": "Movie Tickets" |
| } |
| ``` |
|
|
| ### Data Fields |
|
|
| Each conversation in the data file has the following structure: |
|
|
| - `conversation_id`: A universally unique identifier with the prefix 'dlg-'. The ID has no meaning. |
| - `utterances`: A list of utterances that make up the conversation. |
| - `instructions`: Instructions for the crowdsourced worker used in creating the conversation. |
| - `vertical`: In this dataset the vertical for all dialogs is "Movie Tickets". |
| - `scenario`: This is the title of the instructions for each dialog. |
|
|
| Each utterance has the following fields: |
|
|
| - `index`: A 0-based index indicating the order of the utterances in the conversation. |
| - `speaker`: Either USER or ASSISTANT, indicating which role generated this utterance. |
| - `text`: The raw text of the utterance. In case of self dialogs (one_person_dialogs), this is written by the crowdsourced worker. In case of the WOz dialogs, 'ASSISTANT' turns are written and 'USER' turns are transcribed from the spoken recordings of crowdsourced workers. |
| - `segments`: A list of various text spans with semantic annotations. |
| - `apis`: An array of API invocations made during the utterance. |
|
|
| Each API has the following structure: |
|
|
| - `name`: The name of the API invoked (e.g. find_movies). |
| - `index`: The index of the parent utterance. |
| - `args`: A `list` of `dict` with keys `arg_name` and `arg_value` which represent the name of the argument and the value for the argument respectively. |
| - `response`: A `list` of `dict`s with keys `response_name` and `response_value` which represent the name of the response and the value for the response respectively. |
| |
| Each segment has the following fields: |
| |
| - `start_index`: The position of the start of the annotation in the utterance text. |
| - `end_index`: The position of the end of the annotation in the utterance text. |
| - `text`: The raw text that has been annotated. |
| - `annotations`: A list of annotation details for this segment. |
|
|
| Each annotation has a single field: |
|
|
| - `name`: The annotation name. |
|
|
|
|
|
|
| ### Data Splits |
|
|
| There are no deafults splits for all the config. The below table lists the number of examples in each config. |
|
|
| | | Train | |
| |-------------------|--------| |
| | n_instances | 23757 | |
| |
| |
| ## Dataset Creation |
| |
| ### Curation Rationale |
| |
| [More Information Needed] |
| |
| ### Source Data |
| |
| [More Information Needed] |
| |
| #### Initial Data Collection and Normalization |
| |
| [More Information Needed] |
| |
| #### Who are the source language producers? |
| |
| [More Information Needed] |
| |
| ### Annotations |
| |
| [More Information Needed] |
| |
| #### Annotation process |
| |
| [More Information Needed] |
| |
| #### Who are the annotators? |
| |
| [More Information Needed] |
| |
| ### Personal and Sensitive Information |
| |
| [More Information Needed] |
| |
| ## Considerations for Using the Data |
| |
| ### Social Impact of Dataset |
| |
| [More Information Needed] |
| |
| ### Discussion of Biases |
| |
| [More Information Needed] |
| |
| ### Other Known Limitations |
| |
| [More Information Needed] |
| |
| ## Additional Information |
| |
| ### Dataset Curators |
| |
| [More Information Needed] |
| |
| ### Licensing Information |
| |
| The dataset is licensed under `Creative Commons Attribution 4.0 License` |
| |
| ### Citation Information |
| |
| [More Information Needed] |
| ``` |
| @inproceedings{48484, |
| title = {Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset}, |
| author = {Bill Byrne and Karthik Krishnamoorthi and Chinnadhurai Sankar and Arvind Neelakantan and Daniel Duckworth and Semih Yavuz and Ben Goodrich and Amit Dubey and Kyu-Young Kim and Andy Cedilnik}, |
| year = {2019} |
| } |
| ``` |
| ### Contributions |
| |
| Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset. |
