Triple

T19236237
Position Surface form Disambiguated ID Type / Status
Subject Fremont County Airport E481004 entity
Predicate owner P347 FINISHED
Object Fremont 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: Fremont County | Statement: [Fremont County Airport, owner, Fremont County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fremont County
Context triple: [Fremont County Airport, owner, Fremont County]
  • A. Fremont County
    Fremont County is a rural county in the southwestern corner of Iowa known for its agricultural landscape and small communities.
  • B. Fremont County chosen
    Fremont County is a county in central Colorado known for its rugged terrain, Royal Gorge attractions, and the city of Cañon City as its county seat.
  • C. Sheridan County
    Sheridan County is a rural county in northwestern Kansas known for its agricultural landscape and small communities such as Selden.
  • D. Culberson County
    Culberson County is a sparsely populated county in far western Texas known for its desert landscapes and the Guadalupe Mountains, including the highest peak in the state.
  • E. Laramie County
    Laramie County is a county in southeastern Wyoming that includes the state capital, Cheyenne, and serves as an important governmental and economic center for the region.
  • 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_69d8e8ccb8f48190ad420098e74fb1db completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5faed9ef0819085035cc17d1546e5 completed April 20, 2026, 10:07 a.m.
Created at: April 10, 2026, 1:26 p.m.