Triple

T8858726
Position Surface form Disambiguated ID Type / Status
Subject Dix Stadium E210828 entity
Predicate location P40 FINISHED
Object Kent, Ohio E156899 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: Kent, Ohio | Statement: [Dix Stadium, location, Kent, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kent, Ohio
Context triple: [Dix Stadium, location, Kent, Ohio]
  • A. Kent, Ohio chosen
    Kent, Ohio is a city in northeastern Ohio best known as the home of Kent State University.
  • B. Kettering, Ohio
    Kettering, Ohio is a suburban city near Dayton known for its residential communities, parks, and role as a commercial and cultural hub in the Miami Valley region.
  • C. Dayton, Kentucky
    Dayton, Kentucky is a small Ohio River city in northern Kentucky, located across from Cincinnati and known as part of the greater Cincinnati metropolitan area.
  • D. Covington, Ohio
    Covington, Ohio is a small village in western Ohio known for its rural character and tight-knit community within the Dayton metropolitan area.
  • E. London, Ohio
    London, Ohio is a small city in Madison County that serves as a local commercial and administrative center within the Columbus metropolitan area.
  • 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_69ca838bbddc8190ab546d737e5d350f completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60e536648190ba8da1375478c24f completed April 1, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0b1b86481909ec0b78de043d8f8 completed April 3, 2026, 11:12 a.m.
Created at: March 30, 2026, 6:50 p.m.