Datasets:
mdd

	---
	annotations_creators:
	- no-annotation
	language_creators:
	- found
	language:
	- en
	license:
	- cc-by-3.0
	multilinguality:
	- monolingual
	size_categories:
	- 100K<n<1M
	- 1M<n<10M
	source_datasets:
	- original
	task_categories:
	- text-generation
	- fill-mask
	task_ids:
	- dialogue-modeling
	paperswithcode_id: mdd
	pretty_name: Movie Dialog dataset (MDD)
	dataset_info:
	- config_name: task1_qa
	features:
	- name: dialogue_turns
	sequence:
	- name: speaker
	dtype: int32
	- name: utterance
	dtype: string
	splits:
	- name: train
	num_bytes: 8621120
	num_examples: 96185
	- name: test
	num_bytes: 894590
	num_examples: 9952
	- name: validation
	num_bytes: 892540
	num_examples: 9968
	download_size: 135614957
	dataset_size: 10408250
	- config_name: task2_recs
	features:
	- name: dialogue_turns
	sequence:
	- name: speaker
	dtype: int32
	- name: utterance
	dtype: string
	splits:
	- name: train
	num_bytes: 205936579
	num_examples: 1000000
	- name: test
	num_bytes: 2064509
	num_examples: 10000
	- name: validation
	num_bytes: 2057290
	num_examples: 10000
	download_size: 135614957
	dataset_size: 210058378
	- config_name: task3_qarecs
	features:
	- name: dialogue_turns
	sequence:
	- name: speaker
	dtype: int32
	- name: utterance
	dtype: string
	splits:
	- name: train
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	num_examples: 952125
	- name: test
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	num_examples: 4915
	- name: validation
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	num_examples: 5052
	download_size: 135614957
	dataset_size: 360296161
	- config_name: task4_reddit
	features:
	- name: dialogue_turns
	sequence:
	- name: speaker
	dtype: int32
	- name: utterance
	dtype: string
	splits:
	- name: train
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	num_examples: 945198
	- name: test
	num_bytes: 5220295
	num_examples: 10000
	- name: validation
	num_bytes: 5372702
	num_examples: 10000
	- name: cand_valid
	num_bytes: 1521633
	num_examples: 10000
	- name: cand_test
	num_bytes: 1567235
	num_examples: 10000
	download_size: 192209920
	dataset_size: 511546025
	config_names:
	- task1_qa
	- task2_recs
	- task3_qarecs
	- task4_reddit
	---

	# Dataset Card for MDD

	## 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:[The bAbI project](https://research.fb.com/downloads/babi/)
	- Repository:
	- Paper: [arXiv Paper](https://arxiv.org/pdf/1511.06931.pdf)
	- Leaderboard:
	- Point of Contact:
	### 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 including `0`, `1`, indicating which speaker wrote the utterance.
	- `utterance`: a `string` 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:

	1) MovieLens. The data was downloaded from: http://grouplens.org/datasets/movielens/20m/ on May 27th, 2015.

	2) OMDB. The data was downloaded from: http://beforethecode.com/projects/omdb/download.aspx on May 28th, 2015.

	3) 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](https://github.com/gchhablani) for adding this dataset.