Triple

T1478867
Position Surface form Disambiguated ID Type / Status
Subject Ohio E30904 entity
Predicate hasMajorCity P316 FINISHED
Object Dayton E82485 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: Dayton | Statement: [Ohio, hasMajorCity, Dayton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dayton
Context triple: [Ohio, hasMajorCity, Dayton]
  • A. Dayton
    Dayton is an unincorporated community and census-designated place located within South Brunswick Township in Middlesex County, New Jersey.
  • B. Dayton chosen
    Dayton is a mid-sized city in southwestern Ohio known for its historic role in aviation, manufacturing, and research, including its close association with major U.S. Air Force installations.
  • C. Cincinnati
    Cincinnati is a major city in southwestern Ohio, known for its historic architecture, riverfront location on the Ohio River, and role as a regional economic and cultural center.
  • D. Akron
    Akron is an industrial city in northeastern Ohio known historically for its rubber and tire manufacturing industry.
  • E. Fairborn, Ohio
    Fairborn, Ohio is a city in Greene County that forms part of the Dayton metropolitan area in southwestern Ohio.
  • 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_69a498fe55a88190ab7f9e40ace88e49 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c6739d2481909ea8d8e075f62cf3 completed March 1, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae7198b4948190bd37e4c27f74c817 completed March 9, 2026, 7:07 a.m.
Created at: March 1, 2026, 8:11 p.m.