Triple

T12250
Position Surface form Disambiguated ID Type / Status
Subject Hollywood E247 entity
Predicate hasNearbyNeighborhood P350 FINISHED
Object Los Feliz E12026 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: Los Feliz | Statement: [Hollywood, hasNearbyNeighborhood, Los Feliz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Los Feliz
Context triple: [Hollywood, hasNearbyNeighborhood, Los Feliz]
  • A. West Hollywood
    West Hollywood is an independent city in Los Angeles County known for its vibrant nightlife, LGBTQ+ community, and iconic Sunset Strip.
  • B. 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.
  • C. 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.
  • D. Los Angeles
    Los Angeles is a major U.S. metropolis known for its entertainment industry, cultural diversity, and sprawling urban landscape.
  • E. Central Los Angeles chosen
    Central Los Angeles is a densely populated urban region of the city of Los Angeles known for its historic neighborhoods, cultural landmarks, and major entertainment and commercial districts.
  • 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_69a23d7ad88c8190bffe8ab091d86642 completed Feb. 28, 2026, 12:57 a.m.
NER Named-entity recognition batch_69a2465b2cf881908bf61c461e04cf6a completed Feb. 28, 2026, 1:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69a29e40188c8190a941661f984527bb completed Feb. 28, 2026, 7:50 a.m.
Created at: Feb. 28, 2026, 1:02 a.m.