Triple

T7711040
Position Surface form Disambiguated ID Type / Status
Subject Low Desert E174750 entity
Predicate administrativeRegion P285 FINISHED
Object Imperial County E27589 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: Imperial County | Statement: [Low Desert, administrativeRegion, Imperial County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Imperial County
Context triple: [Low Desert, administrativeRegion, 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 (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_69c6995b3e8c8190833108f883d5f53c completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c702ad6b788190892b96ab523d111f completed March 27, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8accffffc8190b307ad4741e688a8 completed March 29, 2026, 4:38 a.m.
Created at: March 27, 2026, 4:04 p.m.