MovieSum: the dataset card body states Creative Commons Attribution Non Commercial 4.0, but the HF API record has no license tag and the card does not say where the 2,200 screenplays came from. FlawedFictions (kahuja/flawed-fictions): HF tags license MIT, but the card README is empty, so source-sto…

MovieSum: the dataset card body states Creative Commons Attribution Non Commercial 4.0, but the HF API record has no license tag and the card does not say where the 2,200 screenplays came from. FlawedFictions (kahuja/flawed-fictions): HF tags license MIT, but the card README is empty, so source-story provenance is unstated. SummScreen: the repository states no license, GitHub reports none, the data are transcripts and recaps from TV sites, and the archives are Google Drive links. ConStory-Bench: code and dataset are MIT, and the dataset includes generated stories from many LLMs whose providers' output terms the license does not address. The arXiv papers carry CC BY 4.0 (FlawedFictions, Agents' Room, MovieSum) or arXiv's non-exclusive distribution license (ConStory, SCORE, SummScreen, FABLES) for the paper text only. Rationale: Card text, API tags and repository pages were read for each dataset; the absence statements (no license tag, empty README) are observations from those fetches. Counterevidence: A permissive label on the authors' annotations may be valid even where the underlying text rights are unclear; the sources do not say. Uncertainty: Copyright status of the underlying screenplays, transcripts and stories is unresolved (see w2-t01-Q03). Sources: - https://huggingface.co/datasets/rohitsaxena/MovieSum - https://huggingface.co/api/datasets/rohitsaxena/MovieSum - https://huggingface.co/datasets/kahuja/flawed-fictions - https://huggingface.co/api/datasets/kahuja/flawed-fictions - https://github.com/mingdachen/SummScreen - https://huggingface.co/api/datasets/jayden8888/ConStory-Bench - https://arxiv.org/abs/2504.11900 - https://arxiv.org/abs/2408.06281 Checked: 2026-10-17

{
  "context": "What are the license and provenance traps in the narrative-consistency and summarization datasets?"
}