Triple

T11999670
Position Surface form Disambiguated ID Type / Status
Subject Diocese of Sacramento E285622 entity
Predicate territoryIncludes P285 FINISHED
Object Mono County E26068 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: Mono County | Statement: [Diocese of Sacramento, territoryIncludes, Mono County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mono County
Context triple: [Diocese of Sacramento, territoryIncludes, Mono County]
  • A. Mono County chosen
    Mono County is a sparsely populated county in eastern California known for its dramatic Sierra Nevada landscapes, including parts of Yosemite National Park and Mono Lake.
  • B. Morgan County
    Morgan County is a rural county in northeastern Colorado known for its agricultural economy and small communities centered around the city of Fort Morgan.
  • C. Morgan County
    Morgan County is a county in central Indiana, United States, that forms part of the greater Indianapolis metropolitan region.
  • D. Morgan County
    Morgan County is a rural county in the Eastern Panhandle of West Virginia, known for its mountainous terrain, outdoor recreation, and small-town communities.
  • E. Morgan County
    Morgan County is a county in northern Alabama known for its seat in Decatur and its role in the Huntsville-Decatur 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903c26d7881909b67a31d04882eb5 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f472917ed08190a872d9e5663d5ed5 completed May 1, 2026, 9:29 a.m.
Created at: April 8, 2026, 9:46 p.m.