Triple

T11696151
Position Surface form Disambiguated ID Type / Status
Subject Madison County E277998 entity
Predicate borderedBy P224 FINISHED
Object Oneida County E386691 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: Oneida County | Statement: [Madison County, borderedBy, Oneida County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oneida County
Context triple: [Madison County, borderedBy, Oneida County]
  • A. Oneida County chosen
    Oneida County is a county in central New York State, known for its seat in the city of Utica and its role as a regional economic and transportation hub.
  • B. Monroe County
    Monroe County is a rural county in southern West Virginia known for its scenic Appalachian landscapes, agriculture, and historic small towns.
  • C. Monroe County
    Monroe County is a rural county in southwestern Alabama known historically as the home of Monroeville, the hometown of author Harper Lee and a setting that inspired "To Kill a Mockingbird."
  • D. Monroe County
    Monroe County is a county in the U.S. state of Michigan located along the western shore of Lake Erie, south of Detroit.
  • E. Monroe County
    Monroe County is a county in northeastern Pennsylvania known for including part of the Pocono Mountains region.
  • 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_69d6aafe02d881909900d54ad7d4af84 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a47cef60819088b7cc3a3a711e4c completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8b5ad3c81909c38c83804b7d337 completed May 3, 2026, 2:53 a.m.
Created at: April 8, 2026, 9:40 p.m.