Triple

T823421
Position Surface form Disambiguated ID Type / Status
Subject Space Operations Command E17799 entity
Predicate headquartersLocation P62 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: [Space Operations Command, headquartersLocation, Colorado]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colorado
Context triple: [Space Operations Command, headquartersLocation, 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_69a4937c9c188190aaa216f6b466f452 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ab7d3984819089aefbf12d3b3c2c completed March 1, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69adb5a4db2c8190830f3b2a707a3d32 completed March 8, 2026, 5:45 p.m.
Created at: March 1, 2026, 7:38 p.m.