Triple

T458685
Position Surface form Disambiguated ID Type / Status
Subject Mexico Time Zones E7287 entity
Predicate includesRegion P285 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: [Mexico Time Zones, includesRegion, Durango]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Durango
Context triple: [Mexico Time Zones, includesRegion, 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. Santa Fe, New Mexico
    Santa Fe, New Mexico is the capital city of New Mexico, renowned for its Pueblo-style architecture, vibrant arts scene, and rich blend of Native American, Hispanic, and Anglo cultures.
  • C. El Paso
    El Paso is a large border city in far western Texas known for its strong cultural ties with Mexico and its role as a major economic and transportation hub in the region.
  • D. Sedona
    Sedona is a scenic Arizona city famed for its striking red rock formations, vibrant arts community, and reputation as a spiritual and outdoor recreation destination.
  • E. Albuquerque
    Albuquerque is the largest city in New Mexico, known for its high desert landscape, multicultural heritage, and institutions like the University of New Mexico.
  • 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_69a2e7e5c5bc8190a1dc8178218fba40 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2efa4a6208190a8243a0e14f84f52 completed Feb. 28, 2026, 1:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69a452947cd0819084fd885afce26da8 completed March 1, 2026, 2:52 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.