Triple

T2349322
Position Surface form Disambiguated ID Type / Status
Subject Woodstock, Ontario E47408 entity
Predicate isCountySeatOf P383 FINISHED
Object Oxford County E259083 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: Oxford County | Statement: [Woodstock, Ontario, isCountySeatOf, Oxford County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oxford County
Context triple: [Woodstock, Ontario, isCountySeatOf, Oxford County]
  • A. Oxford County chosen
    Oxford County is a regional municipality in southwestern Ontario, Canada, known for its agricultural communities and the city of Woodstock as its largest urban center.
  • B. Auglaize County
    Auglaize County is a county in western Ohio known for its agricultural communities and its county seat, Wapakoneta.
  • C. Greene County
    Greene County is a rural county in western Alabama known for its historical significance in the Black Belt region and its predominantly African American population.
  • D. Greene County
    Greene County is a rural county in eastern New York State known for encompassing a significant portion of the scenic Catskill Mountains.
  • E. 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.
  • 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_69a88a1b678c8190bce986922ba60ce0 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc6cc90d08190824a90e190d1b017 completed March 7, 2026, 6:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea884ac4c8190b484db995251c136 completed March 9, 2026, 11:01 a.m.
Created at: March 4, 2026, 7:54 p.m.