Triple

T6759385
Position Surface form Disambiguated ID Type / Status
Subject Northern Pacific Railway E154551 entity
Predicate helpedDevelop P73 FINISHED
Object Billings, Montana E45126 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: Billings, Montana | Statement: [Northern Pacific Railway, helpedDevelop, Billings, Montana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Billings, Montana
Context triple: [Northern Pacific Railway, helpedDevelop, Billings, Montana]
  • A. Billings chosen
    Billings is the largest city in the U.S. state of Montana and a major economic and cultural hub for the surrounding Mountain States region.
  • B. Billings
    Billings is a small rural municipality located on Manitoulin Island in Ontario, Canada.
  • C. Billings
    Billings is the middle name of Henry Billings Brown, an American jurist who served as an Associate Justice of the U.S. Supreme Court in the late 19th and early 20th centuries.
  • D. Bozeman
    Bozeman is a rapidly growing city in southwestern Montana known for its outdoor recreation, proximity to Yellowstone National Park, and Montana State University.
  • 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_69c6880fd5808190be684854081e27dd completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d21143748190beaab2488971d65b completed March 27, 2026, 6:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72f8c0a3481909f33d2252cc1860c completed March 28, 2026, 1:31 a.m.
Created at: March 27, 2026, 2:12 p.m.