Triple

T88595
Position Surface form Disambiguated ID Type / Status
Subject San Diego–Tijuana E1780 entity
Predicate hasCoreCity P294 FINISHED
Object San Diego E36927 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: San Diego | Statement: [San Diego–Tijuana, hasCoreCity, San Diego]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Diego
Context triple: [San Diego–Tijuana, hasCoreCity, San Diego]
  • A. San Diego chosen
    San Diego is a large coastal city in Southern California known for its mild climate, beaches, naval base, and proximity to the Mexican border.
  • B. 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.
  • C. Irvine
    Irvine is a master-planned city in Orange County, California, known for its affluent residential communities, strong public schools, and concentration of technology and education industries.
  • 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. Santa Ana
    Santa Ana is a major city in Orange County, California, known as a dense urban and governmental center within the Greater Los Angeles metropolitan area.
  • 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_69a24d1a97dc819094e6c021fe9b05a7 completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a24f6997c081908b202f937eb2b14f completed Feb. 28, 2026, 2:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69a39cffe4f08190a8b882137684a931 completed March 1, 2026, 1:57 a.m.
Created at: Feb. 28, 2026, 2:07 a.m.