Triple

T9829689
Position Surface form Disambiguated ID Type / Status
Subject Camp Kearny E238750 entity
Predicate locatedIn P40 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: [Camp Kearny, locatedIn, San Diego]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Diego
Context triple: [Camp Kearny, locatedIn, 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. La Jolla
    La Jolla is an affluent coastal community in Southern California known for its rugged shoreline, beaches, upscale shops, and the University of California, San Diego.
  • C. 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.
  • D. Carlsbad
    Carlsbad is a city in southeastern New Mexico known as the gateway to Carlsbad Caverns National Park.
  • E. Carlsbad
    Carlsbad is a coastal city in northern San Diego County, California, known for its beaches, family attractions like LEGOLAND California, and affluent residential communities.
  • 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_69ca84e0dd1881909800765d1e21f735 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3282a2481908913addf2b3fa58b completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20d048c5081908c891633129dc5d6 completed April 5, 2026, 7:19 a.m.
Created at: March 30, 2026, 8:32 p.m.