Triple

T7765227
Position Surface form Disambiguated ID Type / Status
Subject Dwight Fry E176126 entity
Predicate workedIn P1527 FINISHED
Object Hollywood film industry E247 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: Hollywood film industry | Statement: [Dwight Fry, workedIn, Hollywood film industry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hollywood film industry
Context triple: [Dwight Fry, workedIn, Hollywood film industry]
  • A. Hollywood studios
    Hollywood studios are major American film production companies based in Hollywood that dominate the global movie industry through large-scale financing, production, and distribution of films.
  • B. Hollywood chosen
    Hollywood is a famous Los Angeles neighborhood internationally recognized as the historic center of the American film and entertainment industry.
  • C. Hollywood
    Hollywood is a residential neighborhood in the city of College Park, Maryland, known for its suburban character and proximity to the University of Maryland.
  • D. Hollywood
    Hollywood is a residential neighborhood in Homewood, Alabama, known for its historic homes and suburban character just outside Birmingham.
  • E. Hollywood
    Hollywood is a coastal city in southeastern Florida known for its beaches, boardwalk, and proximity to Miami.
  • 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_69c69962923c8190ac74d28b4f9fe0a0 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7043279748190b30882e9cc6cca54 completed March 27, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7e1a1408190a802d4f4afb8dd05 completed March 29, 2026, 6:34 a.m.
Created at: March 27, 2026, 4:09 p.m.