Triple

T6558561
Position Surface form Disambiguated ID Type / Status
Subject Gladys Brockwell E152513 entity
Predicate workedIn P1527 FINISHED
Object Hollywood 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 | Statement: [Gladys Brockwell, workedIn, Hollywood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hollywood
Context triple: [Gladys Brockwell, workedIn, Hollywood]
  • A. Hollywood chosen
    Hollywood is a famous Los Angeles neighborhood internationally recognized as the historic center of the American film and entertainment industry.
  • B. 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.
  • C. Hollywood
    Hollywood is a residential neighborhood in Homewood, Alabama, known for its historic homes and suburban character just outside Birmingham.
  • D. Hollywood
    Hollywood is a coastal city in southeastern Florida known for its beaches, boardwalk, and proximity to Miami.
  • E. Universal City
    Universal City is a suburban community in the San Antonio metropolitan area of south-central Texas, known for its proximity to Randolph Air Force Base.
  • 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_69c688058d6881908c19b309cc55dbfa completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae202e508190a08a0c0584648b83 completed March 27, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d55c817481908f570b85a6b407f9 completed March 27, 2026, 7:07 p.m.
Created at: March 27, 2026, 1:52 p.m.