Triple

T14575086
Position Surface form Disambiguated ID Type / Status
Subject Knox County, Ohio E342020 entity
Predicate hasVillage P4011 FINISHED
Object Utica, Ohio NE NERFINISHED

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: Utica, Ohio | Statement: [Knox County, Ohio, hasVillage, Utica, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Utica, Ohio
Context triple: [Knox County, Ohio, hasVillage, Utica, Ohio]
  • A. Utica, Ohio chosen
    Utica, Ohio is a small village in central Ohio known for its rural character and annual ice cream festival.
  • B. Urbana, Ohio
    Urbana, Ohio is a small city in Champaign County known for its historic downtown, role as the county seat, and proximity to both Dayton and Springfield in southwestern Ohio.
  • C. Hartford, Ohio
    Hartford, Ohio is a small rural village located in central Ohio within Licking County.
  • D. Wapakoneta, Ohio
    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.
  • E. New London, Ohio
    New London, Ohio is a small village in Huron County known for its rural character and location in north-central Ohio.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb3f49d58819094fcd2a702e146cb completed April 14, 2026, 9:39 p.m.
Created at: April 10, 2026, 1:24 a.m.