Triple

T13702742
Position Surface form Disambiguated ID Type / Status
Subject Fort Apache, The Bronx E328559 entity
Predicate productionCompany P490 FINISHED
Object Time-Life Films E908851 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: Time-Life Films | Statement: [Fort Apache, The Bronx, productionCompany, Time-Life Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Time-Life Films
Context triple: [Fort Apache, The Bronx, productionCompany, Time-Life Films]
  • A. Time-Life Films chosen
    Time-Life Films was a film and television production company associated with Time Inc., known for producing feature films and documentary content in the mid-20th century.
  • B. Davis Films
    Davis Films is a film production company best known for producing genre movies, including entries in the Resident Evil franchise.
  • C. Gilbert Films
    Gilbert Films is an independent film production company known for producing acclaimed feature films and television projects.
  • D. Playfilm Productions
    Playfilm Productions is a film production company best known for producing the acclaimed drama "The Miracle Worker."
  • E. Lippert Films
    Lippert Films was an American independent film distribution and production company active in the mid-20th century, known for handling low-budget genre movies.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dcad162158819089280ee1e6b5c2cf completed April 13, 2026, 8:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69f79459192c81908132ad9813d69125 completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:54 p.m.