Triple

T359805
Position Surface form Disambiguated ID Type / Status
Subject Mines Field E7823 entity
Predicate partOf P40 FINISHED
Object City of Los Angeles E715 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: City of Los Angeles | Statement: [Mines Field, partOf, City of Los Angeles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Los Angeles
Context triple: [Mines Field, partOf, City of Los Angeles]
  • A. Los Angeles chosen
    Los Angeles is a major U.S. metropolis known for its entertainment industry, cultural diversity, and sprawling urban landscape.
  • 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. Downtown Los Angeles
    Downtown Los Angeles is the central business, cultural, and historic core of Los Angeles, known for its skyscrapers, arts and entertainment venues, and diverse neighborhoods.
  • D. Angeles City
    Angeles City is a highly urbanized city in the Philippines’ Pampanga province, known as a commercial and cultural hub in Central Luzon.
  • E. Anaheim
    Anaheim is a major city in Orange County, California, best known as the home of the Disneyland Resort and a significant hub for tourism and entertainment in the region.
  • 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_69a2e7e880008190a6ad7e06e5d03007 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebccb8d88190a31f7c443a0c8566 completed Feb. 28, 2026, 1:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac256a80f08190841759d0f6132e24 completed March 7, 2026, 1:17 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.