Triple

T18678282
Position Surface form Disambiguated ID Type / Status
Subject Model, Colorado E456659 entity
Predicate hasName P744 FINISHED
Object Model, Colorado NE NERFINISHED

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: Model, Colorado | Statement: [Model, Colorado, hasName, Model, Colorado]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Model, Colorado
Context triple: [Model, Colorado, hasName, Model, Colorado]
  • A. Model, Colorado chosen
    Model, Colorado is a small unincorporated community and former railroad town in southeastern Colorado.
  • B. Conifer, Colorado
    Conifer, Colorado is an unincorporated mountain community in Jefferson County known for its forested landscapes, outdoor recreation, and role as a residential area in the foothills southwest of Denver.
  • C. Kim, Colorado
    Kim, Colorado is a small rural town in southeastern Colorado known for its ranching community and remote High Plains setting.
  • D. Morrison, Colorado
    Morrison, Colorado is a small historic town in Jefferson County best known as the gateway to Red Rocks Park and Amphitheatre and for its nearby dinosaur fossil sites.
  • E. Wetmore, Colorado
    Wetmore, Colorado is a small unincorporated community and census-designated place in Custer County known for its rural setting near the Wet Mountains in south-central Colorado.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d391eb488190ac2e9abf5bf255e4 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e55b26cb408190a4e209c0d4ff31ba completed April 19, 2026, 10:45 p.m.
Created at: April 10, 2026, 11:48 a.m.