Triple

T9119600
Position Surface form Disambiguated ID Type / Status
Subject Auglaize County E218809 entity
Predicate hasSettlement P1068 FINISHED
Object Wapakoneta E525467 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: Wapakoneta | Statement: [Auglaize County, hasSettlement, Wapakoneta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wapakoneta
Context triple: [Auglaize County, hasSettlement, Wapakoneta]
  • A. Wapakoneta, Ohio chosen
    Wapakoneta, Ohio is a small city in western Ohio best known as the hometown of astronaut Neil Armstrong and for its strong ties to aerospace history.
  • B. Piqua, Ohio
    Piqua, Ohio is a small city in western Ohio known for its historic downtown, manufacturing heritage, and location along the Great Miami River.
  • C. Wakeman, Ohio
    Wakeman, Ohio is a small village in northern Ohio known for its rural character and location within Huron County.
  • D. Piketon, Ohio
    Piketon, Ohio is a small village in southern Ohio best known for hosting the Portsmouth Gaseous Diffusion Plant, a major former uranium enrichment facility.
  • E. Hudson, Ohio
    Hudson, Ohio is a small city in northeastern Ohio known for its historic New England–style downtown and as a center of education and culture in the 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_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_69d139a887b0819088485006f1653d1c completed April 4, 2026, 4:17 p.m.
Created at: March 30, 2026, 7:17 p.m.