Triple

T19235982
Position Surface form Disambiguated ID Type / Status
Subject Walsenburg Mining Museum E480996 entity
Predicate city P40 FINISHED
Object Walsenburg E110792 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: Walsenburg | Statement: [Walsenburg Mining Museum, city, Walsenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walsenburg
Context triple: [Walsenburg Mining Museum, city, Walsenburg]
  • A. Walsenburg, Colorado chosen
    Walsenburg, Colorado is a small historic city in southern Colorado known as a gateway to the Spanish Peaks and the surrounding high plains and mountain recreation areas.
  • B. Fruita
    Fruita is a small city in western Colorado known for its outdoor recreation, mountain biking trails, and proximity to the Colorado National Monument.
  • C. Silverton
    Silverton is a historic former mining town and popular tourist destination in southwestern Colorado, known for its rugged alpine setting and preserved Old West character.
  • D. Silverton
    Silverton is a small historic city in Marion County, Oregon, known for its charming downtown, proximity to Silver Falls State Park, and strong agricultural roots.
  • E. Silverton
    Silverton is a small town in the Texas Panhandle that serves as the administrative and civic center of Briscoe County.
  • 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_69d8e8ccb8f48190ad420098e74fb1db completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5faed9ef0819085035cc17d1546e5 completed April 20, 2026, 10:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a085a08887c81909f37a39f42ea358a completed May 16, 2026, 11:50 a.m.
Created at: April 10, 2026, 1:26 p.m.