Dataset Card for "cornell_movie_dialog"

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

Languages

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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

Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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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, @patrickvonplaten, @thomwolf for adding this dataset.