Triple

T9035781
Position Surface form Disambiguated ID Type / Status
Subject University of Montana E216489 entity
Predicate locatedIn P40 FINISHED
Object Missoula, Montana E44244 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: Missoula, Montana | Statement: [University of Montana, locatedIn, Missoula, Montana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Missoula, Montana
Context triple: [University of Montana, locatedIn, Missoula, Montana]
  • A. Missoula chosen
    Missoula is a vibrant city in western Montana known for its university, outdoor recreation, and cultural scene.
  • B. Bozeman
    Bozeman is a rapidly growing city in southwestern Montana known for its outdoor recreation, proximity to Yellowstone National Park, and Montana State University.
  • C. Butte, Montana
    Butte, Montana is a historic mining city in southwestern Montana known for its rich copper-mining heritage and well-preserved Old West character.
  • D. Havre, Montana
    Havre, Montana is a small northern Montana city near the Canadian border that serves as a regional commercial and transportation hub on the Hi-Line.
  • E. Libby, Montana
    Libby, Montana is a small northwestern Montana town known for its scenic setting near the Kootenai National Forest and its history of logging and mining.
  • 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_69ca83d10b608190b2b2f8e0a7faaf14 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc6ac0b00c8190a7250b86bb7cc276 completed April 1, 2026, 12:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfeb8ec0588190a24b4a2aa443399f completed April 3, 2026, 4:32 p.m.
Created at: March 30, 2026, 7:08 p.m.