Triple

T12421303
Position Surface form Disambiguated ID Type / Status
Subject Bandera County E296777 entity
Predicate borders P224 FINISHED
Object Kerr County E293861 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: Kerr County | Statement: [Bandera County, borders, Kerr County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kerr County
Context triple: [Bandera County, borders, Kerr County]
  • A. Kerr County chosen
    Kerr County is a rural county in central Texas known for its scenic Hill Country landscapes, outdoor recreation, and the county seat of Kerrville.
  • B. Brewster County
    Brewster County is a vast, sparsely populated county in West Texas known for encompassing much of the Big Bend region along the Rio Grande.
  • C. Nolan County
    Nolan County is a county in west-central Texas known for its wind energy production and county seat, Sweetwater.
  • D. Winkler County
    Winkler County is a sparsely populated, oil-producing county in western Texas known for its desert landscape and small communities such as Kermit.
  • E. Scurry County
    Scurry County is a county in western Texas known for its oil production, agriculture, and county seat of Snyder.
  • 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_69d6ada0640c81908c061d7fb3d47786 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d702b1481909db5f5bed6292ce0 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d445c4848190b5c97bb27be6c749 completed May 10, 2026, 6:53 p.m.
Created at: April 8, 2026, 9:55 p.m.