
# Dataset Card for "cornell_movie_dialog"

## 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:** [http://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html](http://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 9.92 MB
- **Size of the generated dataset:** 19.55 MB
- **Total amount of disk used:** 29.46 MB

### Dataset Summary

This corpus contains a large metadata-rich collection of fictional conversations extracted from raw movie scripts:
- 220,579 conversational exchanges between 10,292 pairs of movie characters
- involves 9,035 characters from 617 movies
- in total 304,713 utterances
- movie metadata included:
    - genres
    - release year
    - IMDB rating
    - number of IMDB votes
    - IMDB rating
- character metadata included:
    - gender (for 3,774 characters)
    - position on movie credits (3,321 characters)

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

#### default

- **Size of downloaded dataset files:** 9.92 MB
- **Size of the generated dataset:** 19.55 MB
- **Total amount of disk used:** 29.46 MB

An example of 'train' looks as follows.
```
{
    "characterID1": "u0 ",
    "characterID2": " u2 ",
    "characterName1": " m0 ",
    "characterName2": " m0 ",
    "movieGenres": ["comedy", "romance"],
    "movieID": " m0 ",
    "movieIMDBRating": " 6.90 ",
    "movieNoIMDBVotes": " 62847 ",
    "movieTitle": " f ",
    "movieYear": " 1999 ",
    "utterance": {
        "LineID": ["L1"],
        "text": ["L1 "]
    }
}
```

### Data Fields

The data fields are the same among all splits.

#### default
- `movieID`: a `string` feature.
- `movieTitle`: a `string` feature.
- `movieYear`: a `string` feature.
- `movieIMDBRating`: a `string` feature.
- `movieNoIMDBVotes`: a `string` feature.
- `movieGenres`: a `list` of `string` features.
- `characterID1`: a `string` feature.
- `characterID2`: a `string` feature.
- `characterName1`: a `string` feature.
- `characterName2`: a `string` feature.
- `utterance`: a dictionary feature containing:
  - `text`: a `string` feature.
  - `LineID`: a `string` feature.

### Data Splits

| name  |train|
|-------|----:|
|default|83097|

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Citation Information

```
  @InProceedings{Danescu-Niculescu-Mizil+Lee:11a,

  author={Cristian Danescu-Niculescu-Mizil and Lillian Lee},

  title={Chameleons in imagined conversations:
  A new approach to understanding coordination of linguistic style in dialogs.},

  booktitle={Proceedings of the

        Workshop on Cognitive Modeling and Computational Linguistics, ACL 2011},

  year={2011}

}

```


### Contributions

Thanks to [@mariamabarham](https://github.com/mariamabarham), [@patrickvonplaten](https://github.com/patrickvonplaten), [@thomwolf](https://github.com/thomwolf) for adding this dataset.
language:en region:us
{"language": ["en"], "paperswithcode_id": "cornell-movie-dialogs-corpus", "pretty_name": "Cornell Movie-Dialogs Corpus", "dataset_info": {"features": [{"name": "movieID", "dtype": "string"}, {"name": "movieTitle", "dtype": "string"}, {"name": "movieYear", "dtype": "string"}, {"name": "movieIMDBRating", "dtype": "string"}, {"name": "movieNoIMDBVotes", "dtype": "string"}, {"name": "movieGenres", "sequence": "string"}, {"name": "characterID1", "dtype": "string"}, {"name": "characterID2", "dtype": "string"}, {"name": "characterName1", "dtype": "string"}, {"name": "characterName2", "dtype": "string"}, {"name": "utterance", "sequence": [{"name": "text", "dtype": "string"}, {"name": "LineID", "dtype": "string"}]}], "splits": [{"name": "train", "num_bytes": 19548840, "num_examples": 83097}], "download_size": 9916637, "dataset_size": 19548840}}
TAGS
#language-English #region-us 

Dataset Card for "cornell\_movie\_dialog"
=========================================


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: URL
* Repository:
* Paper:
* Point of Contact:
* Size of downloaded dataset files: 9.92 MB
* Size of the generated dataset: 19.55 MB
* Total amount of disk used: 29.46 MB


### Dataset Summary


This corpus contains a large metadata-rich collection of fictional conversations extracted from raw movie scripts:


* 220,579 conversational exchanges between 10,292 pairs of movie characters
* involves 9,035 characters from 617 movies
* in total 304,713 utterances
* movie metadata included:
	+ genres
	+ release year
	+ IMDB rating
	+ number of IMDB votes
	+ IMDB rating
* character metadata included:
	+ gender (for 3,774 characters)
	+ position on movie credits (3,321 characters)


### Supported Tasks and Leaderboards


### Languages


Dataset Structure
-----------------


### Data Instances


#### default


* Size of downloaded dataset files: 9.92 MB
* Size of the generated dataset: 19.55 MB
* Total amount of disk used: 29.46 MB


An example of 'train' looks as follows.


### Data Fields


The data fields are the same among all splits.


#### default


* 'movieID': a 'string' feature.
* 'movieTitle': a 'string' feature.
* 'movieYear': a 'string' feature.
* 'movieIMDBRating': a 'string' feature.
* 'movieNoIMDBVotes': a 'string' feature.
* 'movieGenres': a 'list' of 'string' features.
* 'characterID1': a 'string' feature.
* 'characterID2': a 'string' feature.
* 'characterName1': a 'string' feature.
* 'characterName2': a 'string' feature.
* 'utterance': a dictionary feature containing:
	+ 'text': a 'string' feature.
	+ 'LineID': a 'string' feature.


### Data Splits



Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### 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


### Licensing Information


### Contributions


Thanks to @mariamabarham, @patrickvonplaten, @thomwolf for adding this dataset.



### Dataset Summary


This corpus contains a large metadata-rich collection of fictional conversations extracted from raw movie scripts:


* 220,579 conversational exchanges between 10,292 pairs of movie characters
* involves 9,035 characters from 617 movies
* in total 304,713 utterances
* movie metadata included:
	+ genres
	+ release year
	+ IMDB rating
	+ number of IMDB votes
	+ IMDB rating
* character metadata included:
	+ gender (for 3,774 characters)
	+ position on movie credits (3,321 characters) ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### default


* Size of downloaded dataset files: 9.92 MB
* Size of the generated dataset: 19.55 MB
* Total amount of disk used: 29.46 MB


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### default


* 'movieID': a 'string' feature.
* 'movieTitle': a 'string' feature.
* 'movieYear': a 'string' feature.
* 'movieIMDBRating': a 'string' feature.
* 'movieNoIMDBVotes': a 'string' feature.
* 'movieGenres': a 'list' of 'string' features.
* 'characterID1': a 'string' feature.
* 'characterID2': a 'string' feature.
* 'characterName1': a 'string' feature.
* 'characterName2': a 'string' feature.
* 'utterance': a dictionary feature containing:
	+ 'text': a 'string' feature.
	+ 'LineID': a 'string' feature. ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### 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 ### Licensing Information ### Contributions


Thanks to @mariamabarham, @patrickvonplaten, @thomwolf for adding this dataset.
TAGS
#language-English #region-us 
 ### Dataset Summary


This corpus contains a large metadata-rich collection of fictional conversations extracted from raw movie scripts:


* 220,579 conversational exchanges between 10,292 pairs of movie characters
* involves 9,035 characters from 617 movies
* in total 304,713 utterances
* movie metadata included:
	+ genres
	+ release year
	+ IMDB rating
	+ number of IMDB votes
	+ IMDB rating
* character metadata included:
	+ gender (for 3,774 characters)
	+ position on movie credits (3,321 characters) ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### default


* Size of downloaded dataset files: 9.92 MB
* Size of the generated dataset: 19.55 MB
* Total amount of disk used: 29.46 MB


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### default


* 'movieID': a 'string' feature.
* 'movieTitle': a 'string' feature.
* 'movieYear': a 'string' feature.
* 'movieIMDBRating': a 'string' feature.
* 'movieNoIMDBVotes': a 'string' feature.
* 'movieGenres': a 'list' of 'string' features.
* 'characterID1': a 'string' feature.
* 'characterID2': a 'string' feature.
* 'characterName1': a 'string' feature.
* 'characterName2': a 'string' feature.
* 'utterance': a dictionary feature containing:
	+ 'text': a 'string' feature.
	+ 'LineID': a 'string' feature. ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### 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 ### Licensing Information ### Contributions


Thanks to @mariamabarham, @patrickvonplaten, @thomwolf for adding this dataset.