Triple

T9119595
Position Surface form Disambiguated ID Type / Status
Subject Auglaize County E218809 entity
Predicate subdivisionName P747 FINISHED
Object Auglaize County E218809 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: Auglaize County | Statement: [Auglaize County, subdivisionName, Auglaize County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Auglaize County
Context triple: [Auglaize County, subdivisionName, Auglaize County]
  • A. Auglaize County chosen
    Auglaize County is a county in western Ohio known for its agricultural communities and its county seat, Wapakoneta.
  • B. Oxford County
    Oxford County is a largely rural county in western Maine known for its small towns, forests, and outdoor recreation areas.
  • C. Oxford County
    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.
  • D. Ottawa County
    Ottawa County is a county in western Michigan known for its Lake Michigan shoreline, agricultural communities, and cities such as Holland and Grand Haven.
  • E. Lääne County
    Lääne County is a coastal administrative region in western Estonia known for its historic town of Haapsalu and its Baltic Sea shoreline.
  • 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_69ca83dddd548190983b96c664f7f367 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8a902e08190a7eb4728f32b9e1d completed April 1, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d030867d248190ad5b5ba3047426bb completed April 3, 2026, 9:26 p.m.
Created at: March 30, 2026, 7:17 p.m.