Triple

T16664002
Position Surface form Disambiguated ID Type / Status
Subject Taracahitic languages E404932 entity
Predicate geographicDistribution P2178 FINISHED
Object Durango E17928 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 | Statement: [Taracahitic languages, geographicDistribution, Durango]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Durango
Context triple: [Taracahitic languages, geographicDistribution, Durango]
  • A. Durango chosen
    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
    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. Taos
    Taos is a historic town in northern New Mexico known for its rich Native American and Spanish heritage, thriving arts community, and proximity to scenic high-desert and mountain landscapes.
  • E. Pagosa Springs
    Pagosa Springs is a small Colorado town renowned for its natural hot springs and scenic setting in the San Juan Mountains.
  • 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_69d8838b5fbc81908c6575c132b82e80 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37c9afd048190b73bbc9c423915ca completed April 18, 2026, 12:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d31372c8190b9d73a9b7db51f0f completed May 10, 2026, 2:58 p.m.
Created at: April 10, 2026, 5:18 a.m.