Datasets:
The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider
removing the
loading script
and relying on
automated data support
(you can use
convert_to_parquet
from the datasets
library). If this is not possible, please
open a discussion
for direct help.
Dataset Card for MDD
Dataset Summary
The Movie Dialog dataset (MDD) is designed to measure how well models can perform at goal and non-goal orientated dialog centered around the topic of movies (question answering, recommendation and discussion), from various movie reviews sources such as MovieLens and OMDb.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
The data is present in English language as written by users on OMDb and MovieLens websites.
Dataset Structure
Data Instances
An instance from the task3_qarecs
config's train
split:
{'dialogue_turns': {'speaker': [0, 1, 0, 1, 0, 1], 'utterance': ["I really like Jaws, Bottle Rocket, Saving Private Ryan, Tommy Boy, The Muppet Movie, Face/Off, and Cool Hand Luke. I'm looking for a Documentary movie.", 'Beyond the Mat', 'Who is that directed by?', 'Barry W. Blaustein', 'I like Jon Fauer movies more. Do you know anything else?', 'Cinematographer Style']}}
An instance from the task4_reddit
config's cand-valid
split:
{'dialogue_turns': {'speaker': [0], 'utterance': ['MORTAL KOMBAT !']}}
Data Fields
For all configurations:
dialogue_turns
: a dictionary feature containing:speaker
: an integer with possible values including0
,1
, indicating which speaker wrote the utterance.utterance
: astring
feature containing the text utterance.
Data Splits
The splits and corresponding sizes are:
config | train | test | validation | cand_valid | cand_test |
---|---|---|---|---|---|
task1_qa | 96185 | 9952 | 9968 | - | - |
task2_recs | 1000000 | 10000 | 10000 | - | - |
task3_qarecs | 952125 | 4915 | 5052 | - | - |
task4_reddit | 945198 | 10000 | 10000 | 10000 | 10000 |
The cand_valid
and cand_test
are negative candidates for the task4_reddit
configuration which is used in ranking true positive against these candidates and hits@k (or another ranking metric) is reported. (See paper)
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
The construction of the tasks depended on some existing datasets:
MovieLens. The data was downloaded from: http://grouplens.org/datasets/movielens/20m/ on May 27th, 2015.
OMDB. The data was downloaded from: http://beforethecode.com/projects/omdb/download.aspx on May 28th, 2015.
For
task4_reddit
, the data is a processed subset (movie subreddit only) of the data available at: https://www.reddit.com/r/datasets/comments/3bxlg7
Who are the source language producers?
Users on MovieLens, OMDB website and reddit websites, among others.
Annotations
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
Jesse Dodge and Andreea Gane and Xiang Zhang and Antoine Bordes and Sumit Chopra and Alexander Miller and Arthur Szlam and Jason Weston (at Facebook Research).
Licensing Information
Creative Commons Attribution 3.0 License
Citation Information
@misc{dodge2016evaluating,
title={Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems},
author={Jesse Dodge and Andreea Gane and Xiang Zhang and Antoine Bordes and Sumit Chopra and Alexander Miller and Arthur Szlam and Jason Weston},
year={2016},
eprint={1511.06931},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Contributions
Thanks to @gchhablani for adding this dataset.
- Downloads last month
- 105