Triple

T83902
Position Surface form Disambiguated ID Type / Status
Subject Dutchess County E1687 entity
Predicate borders P224 FINISHED
Object Putnam County E15885 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: Putnam County | Statement: [Dutchess County, borders, Putnam County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Putnam County
Context triple: [Dutchess County, borders, Putnam County]
  • A. Putnam County chosen
    Putnam County is a suburban county in southeastern New York State known for its lakes, forests, and commuter communities north of New York City.
  • B. Greene County
    Greene County is a rural county in southwestern Pennsylvania known for its Appalachian landscape, coal mining history, and small-town communities within the greater Pittsburgh region.
  • C. Columbia County
    Columbia County is a rural county in eastern New York State known for its Hudson River frontage, historic towns, and agricultural landscapes.
  • D. Washington County
    Washington County is a county in southwestern Pennsylvania that forms part of the greater Pittsburgh metropolitan area.
  • E. Fayette County
    Fayette County is a largely rural county in southwestern Pennsylvania known for its Appalachian landscape, historic industrial and coal-mining heritage, and proximity to the Pittsburgh 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_69a24c8150408190910a693eb51c1f71 completed Feb. 28, 2026, 2:01 a.m.
NER Named-entity recognition batch_69a24f4e73c081908d2da146226ef05e completed Feb. 28, 2026, 2:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a302803f50819081a480c33f08b68a completed Feb. 28, 2026, 2:58 p.m.
Created at: Feb. 28, 2026, 2:06 a.m.