Triple

T71321
Position Surface form Disambiguated ID Type / Status
Subject Hollywood Sign E1427 entity
Predicate overlooks P1323 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: [Hollywood Sign, overlooks, Hollywood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hollywood
Context triple: [Hollywood Sign, overlooks, 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. Los Angeles
    Los Angeles is a major U.S. metropolis known for its entertainment industry, cultural diversity, and sprawling urban landscape.
  • C. Universal Studios Hollywood
    Universal Studios Hollywood is a major film studio and theme park in Los Angeles known for its movie-based rides, studio tours, and entertainment attractions.
  • D. Long Beach
    Long Beach is a coastal city in Southern California known for its busy port, waterfront attractions, and diverse urban community within the Los Angeles metropolitan area.
  • E. Pasadena
    Pasadena is a city in Los Angeles County, California, known for its scientific and cultural institutions and as the longtime host of the annual Rose Parade and Rose Bowl Game.
  • 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_69a24c06b3bc8190aa4ac89026115efc completed Feb. 28, 2026, 1:59 a.m.
NER Named-entity recognition batch_69a24f0578808190be793d7a161c2cf5 completed Feb. 28, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2981ccdc0819093346109c126ea96 completed Feb. 28, 2026, 7:24 a.m.
Created at: Feb. 28, 2026, 2:03 a.m.