Triple

T12577152
Position Surface form Disambiguated ID Type / Status
Subject Burnet County E300237 entity
Predicate borders P224 FINISHED
Object Blanco County E361293 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: Blanco County | Statement: [Burnet County, borders, Blanco County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blanco County
Context triple: [Burnet County, borders, Blanco County]
  • A. Blanco County chosen
    Blanco County is a rural county in central Texas known for its scenic Hill Country landscapes, small towns, and outdoor recreation along the Blanco River.
  • B. Greenwood County
    Greenwood County is a county in western South Carolina known for its mix of small-city life, manufacturing, and agricultural communities centered around the city of Greenwood.
  • C. Mitchell County
    Mitchell County is a rural county in west-central Texas known for its ranching, wind energy production, and the city of Colorado City as its county seat.
  • D. Llano County
    Llano County is a rural county in central Texas known for its scenic Hill Country landscapes, granite outcrops, and outdoor recreation around lakes and rivers.
  • E. Long County
    Long County is a rural county in southeastern Georgia known for its small population, pine forests, and location within the Hinesville–Fort Stewart 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_69d7bde87b648190bcd0266e9efde098 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954a73c148190bba8f16b1232fd46 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6fef8d94081908ea5ac426e22ef87 completed May 3, 2026, 7:53 a.m.
Created at: April 9, 2026, 4:53 p.m.