Triple

T5516865
Position Surface form Disambiguated ID Type / Status
Subject KPUB E144705 entity
Predicate operator P179 FINISHED
Object City of Pueblo E54832 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: City of Pueblo | Statement: [KPUB, operator, City of Pueblo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Pueblo
Context triple: [KPUB, operator, City of Pueblo]
  • A. City of Pueblo chosen
    The City of Pueblo is a home-rule municipality in southern Colorado that serves as a regional hub for industry, culture, and transportation along the Arkansas River.
  • B. Pueblo
    Pueblo is a city in southern Colorado known for its steel industry heritage, location along the Arkansas River, and diverse cultural history.
  • C. City of San Luis
    The City of San Luis is a municipal government in southwestern Arizona that administers local services and regulations for the border community of San Luis.
  • D. City of Von Ormy
    The City of Von Ormy is a small municipality in south-central Texas known for its location near San Antonio and its experiments with limited government and low-tax policies.
  • E. City of San Pablo
    The City of San Pablo is a small, historically working-class municipality in Contra Costa County, California, located in the East Bay region just north of Richmond.
  • 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_69c008f77ff88190b0cd50ca207295d1 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f5e8ce08190b7f5f2131bebcd4f completed March 22, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027dd848481908052007e89c3f634 completed March 22, 2026, 5:33 p.m.
Created at: March 22, 2026, 3:33 p.m.