Triple

T604955
Position Surface form Disambiguated ID Type / Status
Subject Kansas City metropolitan area E11574 entity
Predicate hasPart P35 FINISHED
Object Belton, Missouri E4804 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: Belton, Missouri | Statement: [Kansas City metropolitan area, hasPart, Belton, Missouri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belton, Missouri
Context triple: [Kansas City metropolitan area, hasPart, Belton, Missouri]
  • A. Belton, Missouri, United States chosen
    Belton, Missouri, United States is a small city in the Kansas City metropolitan area known in part as the burial place of self-improvement pioneer Dale Carnegie.
  • B. Sibley, Missouri
    Sibley, Missouri is a small village in western Missouri known for its proximity to the historic Fort Osage site along the Missouri River.
  • C. Buckner, Missouri
    Buckner, Missouri is a small city located in eastern Jackson County within the Kansas City metropolitan area.
  • D. Gladstone, Missouri
    Gladstone, Missouri is a suburban city in the Kansas City metropolitan area known for its residential neighborhoods and community-oriented services.
  • E. Levasy, Missouri
    Levasy, Missouri is a small rural city located in eastern Jackson County within the Kansas City 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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49dc7d88c81909fe493ac57fd784e completed March 1, 2026, 8:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7cf498af4819085d494f85adf0825 completed March 4, 2026, 6:20 a.m.
Created at: March 1, 2026, 7:35 p.m.