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Datasets:
Rattata
/
screenplay-format-conventions

Languages:
English
Size:
n<1K
Tags:
screenwriting
screenplay
filmmaking
nlp
text-classification
License:
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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
type: string
fountain_pattern: string
fdx_paragraph_type: string
example: string
description: string
format: string
examples: list<item: string>
  child 0, item: string
extensions: list<item: struct<abbreviation: string, meaning: string>>
  child 0, item: struct<abbreviation: string, meaning: string>
      child 0, abbreviation: string
      child 1, meaning: string
rules: list<item: string>
  child 0, item: string
to
{'format': Value('string'), 'extensions': List({'abbreviation': Value('string'), 'meaning': Value('string')}), 'examples': List(Value('string')), 'rules': List(Value('string'))}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              type: string
              fountain_pattern: string
              fdx_paragraph_type: string
              example: string
              description: string
              format: string
              examples: list<item: string>
                child 0, item: string
              extensions: list<item: struct<abbreviation: string, meaning: string>>
                child 0, item: struct<abbreviation: string, meaning: string>
                    child 0, abbreviation: string
                    child 1, meaning: string
              rules: list<item: string>
                child 0, item: string
              to
              {'format': Value('string'), 'extensions': List({'abbreviation': Value('string'), 'meaning': Value('string')}), 'examples': List(Value('string')), 'rules': List(Value('string'))}
              because column names don't match

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Screenplay Format Conventions Dataset

Structured reference data describing the conventions used in Fountain and Final Draft (.fdx) screenplay formats. Useful for:

  • NLP/ML tasks — classifying screenplay elements (scene heading, action, character cue, dialogue, parenthetical, transition)
  • AI pre-production tools — preprocessing scripts for downstream image generation
  • Education — teaching screenplay formatting to junior writers
  • Format converters — building bidirectional Fountain ⇄ FDX tools

Files

  • element_types.json — All screenplay element types with regex patterns and examples
  • scene_heading_grammar.json — INT/EXT prefixes, location patterns, time of day vocabulary
  • transition_keywords.json — Standard transition markers (CUT TO, DISSOLVE TO, FADE OUT, etc.)
  • character_cue_rules.json — Conventions for character names, extensions (V.O., O.S., CONT'D)
  • industry_glossary.json — Common screenwriting terms and abbreviations

License

CC0 — public domain.

Maintained by

STORYLINER — AI storyboard generator. We use the same conventions internally to parse user-uploaded screenplays. Open-source library: github.com/mcqx4/screenplay-parser.
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