Triple

T4825432
Position Surface form Disambiguated ID Type / Status
Subject Tattnall County E107811 entity
Predicate hasBorderWith P224 FINISHED
Object Long County E138755 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: Long County | Statement: [Tattnall County, hasBorderWith, Long County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Long County
Context triple: [Tattnall County, hasBorderWith, Long County]
  • A. Long County chosen
    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.
  • B. 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.
  • C. Blanco County
    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.
  • D. 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.
  • E. Harding County
    Harding County is a sparsely populated rural county in northeastern New Mexico known for its ranching landscape and wide-open high plains.
  • 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_69bd43fac8188190803f0327190621e4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6cadb2bc81909455149e46eb593a completed March 20, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9232aa3081908d08c64d71a9e3cf completed March 21, 2026, 12:42 p.m.
Created at: March 20, 2026, 1:24 p.m.