Triple

T570899
Position Surface form Disambiguated ID Type / Status
Subject West Hollywood E13659 entity
Predicate nickname P55 FINISHED
Object WeHo E13659 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: WeHo | Statement: [West Hollywood, nickname, WeHo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WeHo
Context triple: [West Hollywood, nickname, WeHo]
  • A. Los Feliz
    Los Feliz is a historic and trendy neighborhood in central Los Angeles known for its hillside homes, proximity to Griffith Park, and vibrant dining and nightlife scene.
  • B. West Hollywood chosen
    West Hollywood is an independent city in Los Angeles County known for its vibrant nightlife, LGBTQ+ community, and iconic Sunset Strip.
  • C. Pacific Palisades
    Pacific Palisades is an affluent coastal neighborhood on Los Angeles’ Westside known for its ocean views, canyon landscapes, and small-town feel.
  • D. East Hollywood
    East Hollywood is a diverse, densely populated neighborhood in central Los Angeles known for its mix of residential areas, ethnic enclaves, and proximity to major Hollywood landmarks.
  • E. Hollywood Hills
    Hollywood Hills is a wealthy, hillside residential neighborhood in Los Angeles known for its panoramic city views and iconic association with the entertainment industry.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b483ac08190b3be152a7cf42011 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69acddf440848190aa5019ffcedd4859 completed March 8, 2026, 2:24 a.m.
Created at: March 1, 2026, 7:33 p.m.