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6
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imdb_id
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37.2k
537k
summary
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8MM_1999
tt0134273
"<script>\n <scene>\n <stage_direction>INT. MIAMI AIRPORT, TERMINAL -- DAY</stage_direction>\n (...TRUNCATED)
"Private investigator Tom Welles is contacted by Daniel Longdale, attorney for wealthy widow Mrs. Ch(...TRUNCATED)
The Iron Lady_2011
tt1007029
"<script>\n <scene>\n <stage_direction>INT. SHOP. NR CHESTER SQUARE. LONDON. PRESENT. DAWN.</sta(...TRUNCATED)
"In flashbacks, the audience is shown a young Margaret Roberts working at the family grocer's shop i(...TRUNCATED)
Adventureland_2009
tt1091722
"<script>\n <scene>\n <scene_description>AdVeNtUrElAnD by Greg Mottola revised August 5, 2007 al(...TRUNCATED)
"In 1987, James Brennan plans to have a summer vacation in Europe after graduating from Oberlin Coll(...TRUNCATED)
Napoleon_2023
tt13287846
"<script>\n <scene>\n <character>NAPOLEON</character>\n <dialogue>By</dialogue>\n <scene_d(...TRUNCATED)
"In 1793, amid the French Revolution, young army officer Napoleon Bonaparte watches Marie Antoinette(...TRUNCATED)
Kubo and the Two Strings_2016
tt4302938
"<script>\n <scene>\n <character>KUBO</character>\n <dialogue>... AND THE TWO STRINGS</dialog(...TRUNCATED)
"In feudal Japan, a 12-year-old boy with only one eye named Kubo tends to his ill mother in a mounta(...TRUNCATED)
The Woman King_2022
tt8093700
"<script>\n <scene>\n <character>THE WOMAN KING</character>\n <dialogue>by</dialogue>\n <s(...TRUNCATED)
"In the West African kingdom of Dahomey in 1823, General Nanisca, leader of the all-female tribe of (...TRUNCATED)
What They Had_2018
tt6662736
"<script>\n <scene>\n <character>WHAT THEY HAD</character>\n <dialogue>by</dialogue>\n <sc(...TRUNCATED)
"When Alzheimer's-stricken Ruth Everhardt wanders into the streets during a blizzard on Christmas Ev(...TRUNCATED)
Synecdoche, New York_2008
tt0383028
"<script>\n <scene>\n <scene_description>SYNECDOCHE, NEW YORK by Charlie Kaufman Darkness. The s(...TRUNCATED)
"Theater director Caden Cotard finds his life unraveling. He suffers from numerous physical ailments(...TRUNCATED)
Black Christmas_2006
tt0454082
"<script>\n <scene>\n <scene_description>BI,ACK CHRISTMAS by Glen Morgan Based on the film \"Bfa(...TRUNCATED)
"Billy Lenz is born in 1970, with severe jaundice due to a liver disease, and is constantly abused b(...TRUNCATED)
Superbad_2007
tt0829482
"<script>\n <scene>\n <stage_direction>SUPERBAD</stage_direction>\n <scene_description>OPENIN(...TRUNCATED)
"Seth and Evan are two high school seniors who have been best friends since childhood. The two are a(...TRUNCATED)
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MovieSum: An Abstractive Summarization Dataset for Movie Screenplays

Dataset Summary

MovieSum consists of 2,200 movie screenplays and their corresponding Wikipedia summaries. It is a long-form summarization task where the mean length of movie screenplays is approximately 34K. We manually formatted the movie screenplays to represent their structural elements. We also provide the IMDB ID for each movie to facilitate the collection of additional metadata.

Dataset Statistics

Total Movie Screenplays 2,200
Mean Screenplay Length 34,275
Mean Summary Length 793

Each movie screenplay is in XML format with the following DOM structure:

<script>
<scene>
<stage_direction>..</stage_direction>
<scene_description>...</scene_description>
<character>..</character>
<dialogue>..</dialogue>
...
</scene>
<scene>
...
</scene>
<script>

Dataset Structure

The dataset is divided into three parts:

  • Training Set: 1800 movie screenplays, summaries, and IMDB ids.
  • Validation Set: 200 movie screenplays, summaries, and IMDB ids.
  • Test Set: 200 movie screenplays, summaries, and IMDB ids.

License

Creative Commons Attribution Non Commercial 4.0

Citation

@inproceedings{saxena-keller-2024-moviesum,
    title = "MovieSum: An Abstractive Summarization Dataset for Movie Screenplays",
    author = "Saxena, Rohit  and
      Keller, Frank",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2024",
    month = AUG,
    year = "2024",
    address = "Bangkok, Thailand",
    publisher = "Association for Computational Linguistics",   
}

@misc{saxena2024moviesumabstractivesummarizationdataset,
      title={MovieSum: An Abstractive Summarization Dataset for Movie Screenplays}, 
      author={Rohit Saxena and Frank Keller},
      year={2024},
      eprint={2408.06281},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2408.06281}, 
}

license: cc-by-nc-4.0

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