Triple

T12179934
Position Surface form Disambiguated ID Type / Status
Subject Chicago Basin E290189 entity
Predicate nearestCity P350 FINISHED
Object Durango, Colorado E306961 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: Durango, Colorado | Statement: [Chicago Basin, nearestCity, Durango, Colorado]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Durango, Colorado
Context triple: [Chicago Basin, nearestCity, Durango, Colorado]
  • A. Durango
    Durango is a state in north-central Mexico known for its rugged mountainous terrain, significant mining history, and role as a setting for classic Western films.
  • B. Durango chosen
    Durango is a historic mountain town in southwestern Colorado known for its scenic landscapes, outdoor recreation, and the Durango & Silverton Narrow Gauge Railroad.
  • C. Durango
    Durango is a historic town in the Basque Country of northern Spain, known for its medieval center and cultural heritage.
  • D. Cortez, Colorado
    Cortez, Colorado is a small city in southwestern Colorado known as a gateway to Mesa Verde National Park and the Four Corners region.
  • E. Alamosa, Colorado
    Alamosa, Colorado is a small city in the San Luis Valley known as a regional hub for southern Colorado and a gateway to Great Sand Dunes National Park.
  • 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_69d6ab64de5881908d56eb7a75c6cc69 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d915fc451c819086a2a97967b82908 completed April 10, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6ab19288190a882c842d74a2e30 completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:50 p.m.