MovieSum: An Abstractive Summarization Dataset for Movie Screenplays
Movie screenplay summarization is challenging, as it requires an
understanding of long input contexts and various elements unique to movies.
Large language models have shown significant advancements in document
summarization, but they often struggle with processing long input contexts.
Furthermore, while television transcripts have received attention in recent
studies, movie screenplay summarization remains underexplored. To stimulate
research in this area, we present a new dataset, MovieSum, for abstractive
summarization of movie screenplays. This dataset comprises 2200 movie
screenplays accompanied by their Wikipedia plot summaries. We manually
formatted the movie screenplays to represent their structural elements.
Compared to existing datasets, MovieSum possesses several distinctive features:
(1) It includes movie screenplays, which are longer than scripts of TV
episodes. (2) It is twice the size of previous movie screenplay datasets. (3)
It provides metadata with IMDb IDs to facilitate access to additional external
knowledge. We also show the results of recently released large language models
applied to summarization on our dataset to provide a detailed baseline.
66bc35255ee1c61552bccf46
Rohit Saxena
claimed_verified
2024-08-14T08:11:24.657Z
657ccbf2869d5bb0e53b482f
/avatars/2eae5a10bdc14814a04d9f255f16de6b.svg
Rohit Saxena
user
rohitsaxena
66bc35255ee1c61552bccf47
Frank Keller
admin_assigned
2024-08-14T11:05:48.721Z
632f501c310d1b5d94a5b714
/avatars/e835860128623a40de065f247f33262e.svg
Frank Keller
user
kellerfe
MovieSum: An Abstractive Summarization Dataset for Movie Screenplays
Movie screenplay summarization is challenging, as it requires an
understanding of long input contexts and various elements unique to movies.
Large language models have shown significant advancements in document
summarization, but they often struggle with processing long input contexts.
Furthermore, while television transcripts have received attention in recent
studies, movie screenplay summarization remains underexplored. To stimulate
research in this area, we present a new dataset, MovieSum, for abstractive
summarization of movie screenplays. This dataset comprises 2200 movie
screenplays accompanied by their Wikipedia plot summaries. We manually
formatted the movie screenplays to represent their structural elements.
Compared to existing datasets, MovieSum possesses several distinctive features:
(1) It includes movie screenplays, which are longer than scripts of TV
episodes. (2) It is twice the size of previous movie screenplay datasets. (3)
It provides metadata with IMDb IDs to facilitate access to additional external
knowledge. We also show the results of recently released large language models
applied to summarization on our dataset to provide a detailed baseline.
A new dataset, MovieSum, is introduced for abstractive summarization of movie screenplays, addressing challenges in processing long contexts and underlining the lack of research in this area compared to television transcripts.
abstractive summarization movie screenplays long input contexts television transcripts Wikipedia plot summaries IMDb IDs large language models