Triple

T16230759
Position Surface form Disambiguated ID Type / Status
Subject Carbon County E393972 entity
Predicate borders P224 FINISHED
Object Lehigh County NE NERFINISHED

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: Lehigh County | Statement: [Carbon County, borders, Lehigh County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lehigh County
Context triple: [Carbon County, borders, Lehigh County]
  • A. Lehigh County, Pennsylvania chosen
    Lehigh County, Pennsylvania is a county in eastern Pennsylvania known for its largest city, Allentown, and its role as part of the Lehigh Valley metropolitan region.
  • B. Luzerne County
    Luzerne County is a county in northeastern Pennsylvania known for its seat in Wilkes-Barre and its role in the historic anthracite coal mining region.
  • C. Chester County
    Chester County is a county in northern South Carolina that forms part of the greater Charlotte metropolitan region.
  • D. Susquehanna County
    Susquehanna County is a rural county in northeastern Pennsylvania known for its rolling hills, small towns, and proximity to the New York state border.
  • E. Chester County, Pennsylvania
    Chester County, Pennsylvania is a suburban and semi-rural county in southeastern Pennsylvania known for its historic towns, scenic landscapes, and role as part of the greater Philadelphia metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d87f204df88190a8f88923decf9835 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e23d29438c81909aa2724cc47bb959 completed April 17, 2026, 2:01 p.m.
Created at: April 10, 2026, 5:03 a.m.