Triple

T15940178
Position Surface form Disambiguated ID Type / Status
Subject Upton County E386536 entity
Predicate borderedBy P224 FINISHED
Object Midland County E264393 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: Midland County | Statement: [Upton County, borderedBy, Midland County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Midland County
Context triple: [Upton County, borderedBy, Midland County]
  • A. Midland County chosen
    Midland County is a county in western Texas centered around the city of Midland, a major hub for the Permian Basin oil and gas industry.
  • B. Midland County
    Midland County is a county in central Michigan known for its role in the Great Lakes Bay Region and as the home of the city of Midland and major chemical industry operations.
  • 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. Lawrence County
    Lawrence County is a rural county in central Mississippi known for its small communities, forests, and agricultural landscape.
  • E. Lawrence County
    Lawrence County is a county in western South Dakota known for including part of the Black Hills region and the historic city of Deadwood.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156cd3a188190a1a7dcbfdd38284c completed April 16, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d25abec8190954b640b63efa0c2 completed May 10, 2026, 2:58 p.m.
Created at: April 10, 2026, 4:53 a.m.