Triple

T10079909
Position Surface form Disambiguated ID Type / Status
Subject Killeen, Texas E213872 entity
Predicate nearbyCity P350 FINISHED
Object Temple, Texas E341976 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: Temple, Texas | Statement: [Killeen, Texas, nearbyCity, Temple, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Temple, Texas
Context triple: [Killeen, Texas, nearbyCity, Temple, Texas]
  • A. Temple, Texas chosen
    Temple, Texas is a central Texas city known for its major medical and educational institutions, including significant healthcare and research facilities.
  • B. Moody, Texas
    Moody, Texas is a small rural city in Central Texas known for its close-knit community and agricultural surroundings.
  • C. Taylor, Texas
    Taylor, Texas is a small city in central Texas known for its historic downtown, agricultural roots, and location within the Greater Austin metropolitan area.
  • D. Tatum, Texas
    Tatum, Texas is a small city in East Texas known for its rural character and location near the intersection of major regional highways.
  • E. Cottonwood, Texas
    Cottonwood, Texas is a small rural community located within Kaufman County in the state of Texas.
  • 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd031ce748190bb71189afd331979 completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d3174109988190b703bb5b7c89c5c2 completed April 6, 2026, 2:15 a.m.
Created at: March 30, 2026, 9 p.m.