Triple

T16192188
Position Surface form Disambiguated ID Type / Status
Subject Yates County E392968 entity
Predicate borders P224 FINISHED
Object Schuyler County E420477 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: Schuyler County | Statement: [Yates County, borders, Schuyler County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schuyler County
Context triple: [Yates County, borders, Schuyler County]
  • A. Schuyler County chosen
    Schuyler County is a rural county in New York State’s Finger Lakes region, known for its scenic landscapes, wineries, and outdoor recreation.
  • B. Warren County
    Warren County is a largely rural county in northwestern New Jersey known for its small towns, farmland, and role as a residential area for commuters in the New York metropolitan region.
  • C. Warren County
    Warren County is a county-level jurisdiction in Kentucky that includes the city of Bowling Green and oversees various local public facilities and services.
  • D. Warren County
    Warren County is a county in western Mississippi known for its seat, the historic river city of Vicksburg, a key site in the American Civil War.
  • E. Warren County
    Warren County is a rural county in northwestern Pennsylvania known for its forests, outdoor recreation, and location along the Allegheny River.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222d6975c8190a512a65d5b0021bb completed April 17, 2026, 12:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f860ecc8190be904fa793968d89 completed May 10, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:02 a.m.