Triple

T2464445
Position Surface form Disambiguated ID Type / Status
Subject Ruth Rose E55210 entity
Predicate activeIn P1560 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: [Ruth Rose, activeIn, Hollywood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hollywood
Context triple: [Ruth Rose, activeIn, Hollywood]
  • A. 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.
  • 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 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, California
    Universal City, California is an unincorporated community in Los Angeles County best known as the home of the Universal Studios film studio and theme park complex.
  • 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_69ab49e3622c8190ad22afa2c4fbb807 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd1216f44819094c46ae7c2c1e394 completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69af177b898c8190bee910be75e93f6c completed March 9, 2026, 6:54 p.m.
Created at: March 6, 2026, 9:44 p.m.