Triple

T20597210
Position Surface form Disambiguated ID Type / Status
Subject Mineral County, Montana E506080 entity
Predicate countrySubdivisionOf P766 FINISHED
Object Montana 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: Montana | Statement: [Mineral County, Montana, countrySubdivisionOf, Montana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montana
Context triple: [Mineral County, Montana, countrySubdivisionOf, Montana]
  • A. Montana chosen
    Montana is a large, sparsely populated U.S. state in the northern Rocky Mountains known for its expansive wilderness, national parks like Glacier, and wide-open "Big Sky" landscapes.
  • B. Montana
    Montana is a small city in northwestern Bulgaria known as a regional administrative and economic center near the foothills of the Balkan Mountains.
  • C. Montana
    Montana was a former Swiss alpine resort municipality that later became part of the larger resort area of Crans-Montana in the canton of Valais.
  • D. Wyoming
    Wyoming is a sparsely populated U.S. state known for its vast plains, the Rocky Mountains, and iconic national parks like Yellowstone and Grand Teton.
  • E. Wyoming
    Wyoming is a small borough in Luzerne County, Pennsylvania, situated in the historic Wyoming Valley along the Susquehanna River.
  • 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_69e0b4ba6ae88190af871e1f9522c704 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6aa1d15b08190a720fc7cefbf333e completed April 20, 2026, 10:35 p.m.
Created at: April 16, 2026, 11:40 a.m.