Triple

T9305733
Position Surface form Disambiguated ID Type / Status
Subject Rocky Mountain High E223879 entity
Predicate subject P450 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: [Rocky Mountain High, subject, Colorado]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colorado
Context triple: [Rocky Mountain High, subject, 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. D. Colo.
    D. Colo. is the standard legal abbreviation for the United States District Court for the District of Colorado, a federal trial court within the Tenth Circuit.
  • C. 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.
  • D. Arizona
    "Arizona" is a 2018 dark comedy thriller film set during the 2009 housing crisis, starring Rosemarie DeWitt and Danny McBride.
  • E. Arizona
    Arizona is a southwestern U.S. state known for its desert climate, the Grand Canyon, and major cities like Phoenix and Tucson.
  • 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_69ca8424d0f08190831e2e93c6533aeb completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd1da7c1e08190af19169f5d806cde completed April 1, 2026, 1:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0c72be25c8190931204b21966502e completed April 4, 2026, 8:09 a.m.
Created at: March 30, 2026, 7:36 p.m.