Triple

T8694960
Position Surface form Disambiguated ID Type / Status
Subject Temple, Texas E206383 entity
Predicate locatedNear P294 FINISHED
Object Belton, Texas E404260 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, Texas | Statement: [Temple, Texas, locatedNear, Belton, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belton, Texas
Context triple: [Temple, Texas, locatedNear, Belton, Texas]
  • A. Belton, Texas chosen
    Belton, Texas is a small central Texas city known as the county seat of Bell County and part of the Killeen–Temple metropolitan area.
  • B. Burleson, Texas
    Burleson, Texas is a growing suburban city in the Dallas–Fort Worth metropolitan area known for its family-friendly neighborhoods and proximity to Fort Worth.
  • C. Bullard, Texas
    Bullard, Texas is a small town in East Texas that serves as a suburban community within the greater Tyler metropolitan area.
  • D. Bellmead, Texas
    Bellmead, Texas is a small city in Central Texas that functions as a suburb of Waco.
  • E. Mount Pleasant, Texas
    Mount Pleasant, Texas is a small city in northeastern Texas that serves as a regional commercial and cultural hub within the Ark-La-Tex 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_69ca83555b6c8190abe930dd397e863b completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc58284c58819091beb05a7d6b3a1b completed March 31, 2026, 11:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef3f36a6081909e300f168fbcb8ac completed April 2, 2026, 10:55 p.m.
Created at: March 30, 2026, 6:33 p.m.