Triple

T9778066
Position Surface form Disambiguated ID Type / Status
Subject Mr. Holmes E237294 entity
Predicate productionCompany P490 FINISHED
Object See-Saw Films E11869 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: See-Saw Films | Statement: [Mr. Holmes, productionCompany, See-Saw Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: See-Saw Films
Context triple: [Mr. Holmes, productionCompany, See-Saw Films]
  • A. See-Saw Films chosen
    See-Saw Films is a British-Australian film and television production company known for acclaimed works such as the Academy Award–winning drama "The King’s Speech."
  • B. Blossom Films
    Blossom Films is a film and television production company founded by actress Nicole Kidman, known for developing high-profile, character-driven projects.
  • C. Waverly Films
    Waverly Films is a Brooklyn-based film and video production collective known for its offbeat comedy shorts, music videos, and collaborations with major studios and brands.
  • D. Overture Films
    Overture Films was an American independent film production and distribution company active in the late 2000s, known for releasing a range of mid-budget and specialty films.
  • E. Silverwood Films
    Silverwood Films is an independent film production company known for backing critically acclaimed dramas such as "Blue Valentine."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca84d975a08190aab25b02a89bdab3 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda13545808190a47544b0cc666e20 completed April 1, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc4950f48190be84bb57f7f453ef completed April 5, 2026, 2:43 a.m.
Created at: March 30, 2026, 8:26 p.m.