Triple

T622685
Position Surface form Disambiguated ID Type / Status
Subject Front Range Urban Corridor E14547 entity
Predicate locatedIn P40 FINISHED
Object Colorado E42836 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: Colorado | Statement: [Front Range Urban Corridor, locatedIn, Colorado]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colorado
Context triple: [Front Range Urban Corridor, locatedIn, Colorado]
  • A. Colorado chosen
    Colorado is a landlocked U.S. state known for its Rocky Mountain landscapes, outdoor recreation, and cities like Denver and Boulder.
  • B. Utah
    Utah is a landlocked state in the western United States known for its vast deserts, distinctive red rock landscapes, and prominent national parks such as Zion and Arches.
  • C. Arizona
    Arizona is a southwestern U.S. state known for its desert climate, the Grand Canyon, and major cities like Phoenix and Tucson.
  • D. New Mexico
    New Mexico is a southwestern U.S. state known for its diverse landscapes, rich Native American and Hispanic cultural heritage, and historic cities like Santa Fe and Albuquerque.
  • E. Wyoming
    Wyoming is a sparsely populated U.S. state known for its vast plains, the Rocky Mountains, and iconic national parks like Yellowstone and Grand Teton.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e402d9c8190936896e3ebb6edc5 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad4678de4481908d6a0e6325e0a0e0 completed March 8, 2026, 9:50 a.m.
Created at: March 1, 2026, 7:35 p.m.