
# 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.
task_categories:text-generation task_categories:fill-mask task_ids:dialogue-modeling annotations_creators:no-annotation language_creators:found multilinguality:monolingual size_categories:100K<n<1M size_categories:1M<n<10M source_datasets:original language:en license:cc-by-3.0 arxiv:1511.06931 region:us
{"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)", "config_names": ["task1_qa", "task2_recs", "task3_qarecs", "task4_reddit"], "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", "num_bytes": 356789364, "num_examples": 952125}, {"name": "test", "num_bytes": 1730291, "num_examples": 4915}, {"name": "validation", "num_bytes": 1776506, "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", "num_bytes": 497864160, "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}]}
TAGS
#task_categories-text-generation #task_categories-fill-mask #task_ids-dialogue-modeling #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #size_categories-1M<n<10M #source_datasets-original #language-English #license-cc-by-3.0 #arxiv-1511.06931 #region-us 

Dataset Card for MDD
====================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ Personal and Sensitive Information
* Considerations for Using the Data
	+ Social Impact of Dataset
	+ Discussion of Biases
	+ Other Known Limitations
* Additional Information
	+ Dataset Curators
	+ Licensing Information
	+ Citation Information
	+ Contributions


Dataset Description
-------------------


* Homepage:The bAbI project
* Repository:
* Paper: arXiv Paper
* 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


### 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:


An instance from the 'task4\_reddit' config's 'cand-valid' split:


### 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:



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


### Source Data


#### Initial Data Collection and Normalization


The construction of the tasks depended on some existing datasets:


1. MovieLens. The data was downloaded from: URL on May 27th, 2015.
2. OMDB. The data was downloaded from: URL on May 28th, 2015.
3. For 'task4\_reddit', the data is a processed subset (movie subreddit only) of the data available at:
URL


#### Who are the source language producers?


Users on MovieLens, OMDB website and reddit websites, among others.


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


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


### Contributions


Thanks to @gchhablani for adding this dataset.



### 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 ### 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:


An instance from the 'task4\_reddit' config's 'cand-valid' split: ### 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:



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 ### Source Data #### Initial Data Collection and Normalization


The construction of the tasks depended on some existing datasets:


1. MovieLens. The data was downloaded from: URL on May 27th, 2015.
2. OMDB. The data was downloaded from: URL on May 28th, 2015.
3. For 'task4\_reddit', the data is a processed subset (movie subreddit only) of the data available at:
URL #### Who are the source language producers?


Users on MovieLens, OMDB website and reddit websites, among others. ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


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 ### Contributions


Thanks to @gchhablani for adding this dataset.
TAGS
#task_categories-text-generation #task_categories-fill-mask #task_ids-dialogue-modeling #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #size_categories-1M<n<10M #source_datasets-original #language-English #license-cc-by-3.0 #arxiv-1511.06931 #region-us 
 ### 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 ### 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:


An instance from the 'task4\_reddit' config's 'cand-valid' split: ### 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:



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 ### Source Data #### Initial Data Collection and Normalization


The construction of the tasks depended on some existing datasets:


1. MovieLens. The data was downloaded from: URL on May 27th, 2015.
2. OMDB. The data was downloaded from: URL on May 28th, 2015.
3. For 'task4\_reddit', the data is a processed subset (movie subreddit only) of the data available at:
URL #### Who are the source language producers?


Users on MovieLens, OMDB website and reddit websites, among others. ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


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 ### Contributions


Thanks to @gchhablani for adding this dataset.
passage: TAGS
#task_categories-text-generation #task_categories-fill-mask #task_ids-dialogue-modeling #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #size_categories-1M<n<10M #source_datasets-original #language-English #license-cc-by-3.0 #arxiv-1511.06931 #region-us 
### 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### 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:


An instance from the 'task4\_reddit' config's 'cand-valid' split:### 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:



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### Source Data