Triple

T1318542
Position Surface form Disambiguated ID Type / Status
Subject City Lights E28161 entity
Predicate hasFilmLocation P4373 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: [City Lights, hasFilmLocation, Hollywood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hollywood
Context triple: [City Lights, hasFilmLocation, 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. 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.
  • E. West Hollywood
    West Hollywood is an independent city in Los Angeles County known for its vibrant nightlife, LGBTQ+ community, and iconic Sunset Strip.
  • 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_69a498532c3481909223b74af2e578df completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c48d25608190b069fb4d0d460aa6 completed March 1, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbad55a4c8190977e8e5d313c56df completed March 7, 2026, 11:55 p.m.
Created at: March 1, 2026, 7:55 p.m.