Triple

T22786877
Position Surface form Disambiguated ID Type / Status
Subject CIF San Diego Section E563991 entity
Predicate jurisdiction P82 FINISHED
Object Imperial County NE NERFINISHED

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: Imperial County | Statement: [CIF San Diego Section, jurisdiction, Imperial County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Imperial County
Context triple: [CIF San Diego Section, jurisdiction, Imperial County]
  • A. Imperial County chosen
    Imperial County is a largely agricultural and desert county in southeastern California, bordering Mexico and known for the Imperial Valley and the Salton Sea.
  • B. Torrance County
    Torrance County is a largely rural county in central New Mexico known for its high plains landscape and small, dispersed communities.
  • C. Mariposa County
    Mariposa County is a rural county in central California best known as the gateway to much of Yosemite National Park and the Sierra Nevada.
  • D. Lassen County
    Lassen County is a rural county in northeastern California known for its volcanic landscapes, high desert terrain, and proximity to Lassen Volcanic National Park.
  • E. Kern County
    Kern County is a large, oil- and agriculture-rich county in California’s southern Central Valley that includes cities such as Bakersfield and is a major hub for energy production.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2455500788190b4b33030461f3bbd completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17c321f848190a4443aa6bb4e57d7 completed April 29, 2026, 3:34 a.m.
Created at: April 17, 2026, 3:29 p.m.