Triple

T14764390
Position Surface form Disambiguated ID Type / Status
Subject Mantua, Ohio E346955 entity
Predicate nearbyCity P350 FINISHED
Object Ravenna, 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: Ravenna, Ohio | Statement: [Mantua, Ohio, nearbyCity, Ravenna, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ravenna, Ohio
Context triple: [Mantua, Ohio, nearbyCity, Ravenna, Ohio]
  • A. Ravenna, Ohio chosen
    Ravenna, Ohio is a small city in northeastern Ohio that serves as the county seat of Portage County and is part of the Akron metropolitan area.
  • B. Dublin, Ohio
    Dublin, Ohio is a suburban city northwest of Columbus known for its affluent neighborhoods, strong school system, and annual Dublin Irish Festival.
  • C. Dresden, Ohio
    Dresden, Ohio is a small village in Muskingum County known historically as the original home of the Longaberger Company and its handcrafted baskets.
  • D. Havana, Ohio
    Havana, Ohio is a small unincorporated community located in Huron County in north-central Ohio.
  • E. Genoa, Ohio
    Genoa, Ohio is a small village in northern Ohio known for its rural community character and location within the Toledo metropolitan area.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7f3a1608190b1b17624003a0c7f completed April 14, 2026, 11:04 p.m.
Created at: April 10, 2026, 1:30 a.m.