Triple

T11101014
Position Surface form Disambiguated ID Type / Status
Subject Central Ohio E262502 entity
Predicate hasMajorCity P316 FINISHED
Object Dublin, Ohio E403147 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: Dublin, Ohio | Statement: [Central Ohio, hasMajorCity, Dublin, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dublin, Ohio
Context triple: [Central Ohio, hasMajorCity, Dublin, Ohio]
  • A. Dublin, Ohio chosen
    Dublin, Ohio is a suburban city northwest of Columbus known for its affluent neighborhoods, strong school system, and annual Dublin Irish Festival.
  • B. 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.
  • C. Havana, Ohio
    Havana, Ohio is a small unincorporated community located in Huron County in north-central Ohio.
  • D. Geneva, Ohio
    Geneva, Ohio is a small city in northeastern Ohio best known as the birthplace of automobile pioneer Ransom E. Olds.
  • E. Wilmington, Ohio
    Wilmington, Ohio is a small city in southwestern Ohio known historically as a regional transportation hub and home to a major air park and agricultural community.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a2ab09081908ffce2df8912b657 completed April 9, 2026, 12:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69feadf5e520819090c3211a1992d463 completed May 9, 2026, 3:45 a.m.
Created at: April 8, 2026, 9:27 p.m.