summscreen

  • Description:

SummScreen Summarization dataset, non-anonymized, non-tokenized version.

Train/val/test splits and filtering are based on the final tokenized dataset, but transcripts and recaps provided are based on the untokenized text.

There are two features:

@article{DBLP:journals/corr/abs-2104-07091,
  author    = {Mingda Chen and
               Zewei Chu and
               Sam Wiseman and
               Kevin Gimpel},
  title     = {SummScreen: {A} Dataset for Abstractive Screenplay Summarization},
  journal   = {CoRR},
  volume    = {abs/2104.07091},
  year      = {2021},
  url       = {https://arxiv.org/abs/2104.07091},
  archivePrefix = {arXiv},
  eprint    = {2104.07091},
  timestamp = {Mon, 19 Apr 2021 16:45:47 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2104-07091.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

summscreen/fd (default config)

  • Config description: ForeverDreaming

  • Dataset size: 132.99 MiB

  • Auto-cached (documentation): Yes

  • Splits:

Split Examples
'test' 337
'train' 3,673
'validation' 338
  • Feature structure:
FeaturesDict({
    'episode_number': Text(shape=(), dtype=string),
    'episode_title': Text(shape=(), dtype=string),
    'recap': Text(shape=(), dtype=string),
    'show_title': Text(shape=(), dtype=string),
    'transcript': Text(shape=(), dtype=string),
    'transcript_author': Text(shape=(), dtype=string),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
episode_number Text string
episode_title Text string
recap Text string
show_title Text string
transcript Text string
transcript_author Text string

summscreen/tms

  • Config description: TVMegaSite

  • Dataset size: 592.53 MiB

  • Auto-cached (documentation): No

  • Splits:

Split Examples
'test' 1,793
'train' 18,915
'validation' 1,795
  • Feature structure:
FeaturesDict({
    'episode_summary': Text(shape=(), dtype=string),
    'recap': Text(shape=(), dtype=string),
    'recap_author': Text(shape=(), dtype=string),
    'show_title': Text(shape=(), dtype=string),
    'transcript': Text(shape=(), dtype=string),
    'transcript_author': Tensor(shape=(None,), dtype=string),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
episode_summary Text string
recap Text string
recap_author Text string
show_title Text string
transcript Text string
transcript_author Tensor (None,) string