Triple

T5120519
Position Surface form Disambiguated ID Type / Status
Subject Wamego City Park E115449 entity
Predicate operatedBy P86 FINISHED
Object City of Wamego E429631 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 Wamego | Statement: [Wamego City Park, operatedBy, City of Wamego]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Wamego
Context triple: [Wamego City Park, operatedBy, City of Wamego]
  • A. City of Wamego chosen
    The City of Wamego is a municipal government in Kansas that oversees local services, infrastructure, and community institutions for residents of the Wamego area.
  • B. Florenville
    Florenville is a picturesque town in southern Belgium’s Wallonia region, known for its scenic setting along the Semois River and surrounding Ardennes landscapes.
  • C. City of Watseka
    City of Watseka is a small municipal community in Iroquois County in eastern Illinois, serving as the county seat and local economic center.
  • D. Mebanesville
    Mebanesville was the original name of the city now known as Mebane in North Carolina.
  • E. City of Monroe
    The City of Monroe is a municipal government in northeastern Louisiana that serves as the administrative and cultural center of the Monroe metropolitan area.
  • 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_69bd4442ade0819087b9461f892b206b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd78015ad88190a3e51da494c19e30 completed March 20, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69bec4b0578c819081ad7554bafafe49 completed March 21, 2026, 4:17 p.m.
Created at: March 20, 2026, 1:42 p.m.