Triple

T10905617
Position Surface form Disambiguated ID Type / Status
Subject Magic City E257560 entity
Predicate geographicRegion P285 FINISHED
Object Yellowstone County E268737 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: Yellowstone County | Statement: [Magic City, geographicRegion, Yellowstone County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yellowstone County
Context triple: [Magic City, geographicRegion, Yellowstone County]
  • A. Yellowstone County chosen
    Yellowstone County is a county in south-central Montana, United States, known for being the state’s most populous county and home to the city of Billings.
  • B. Park County
    Park County is a rural county in southwestern Montana known for its proximity to Yellowstone National Park and its scenic mountain landscapes.
  • C. Park County
    Park County is a county in northwestern Wyoming known for encompassing portions of Yellowstone National Park and its surrounding mountainous landscapes.
  • D. Custer County
    Custer County is a county in southwestern South Dakota known for its Black Hills scenery, outdoor recreation, and attractions such as Custer State Park and the Crazy Horse Memorial.
  • E. Custer County
    Custer County is a rural county in south-central Colorado known for its scenic Wet Mountain Valley, ranching heritage, and outdoor recreation opportunities in the surrounding Wet Mountains and Sangre de Cristo Range.
  • 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_69d6aa8550c8819095508a2ed9acf3db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770656c288190828e71600bb0acd4 completed April 9, 2026, 9:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3e6e88e508190a1bcd90cc67cbbbf completed April 18, 2026, 8:17 p.m.
Created at: April 8, 2026, 9:22 p.m.