Triple

T15418873
Position Surface form Disambiguated ID Type / Status
Subject Zapp E369319 entity
Predicate locationOfFormation P3743 FINISHED
Object Dayton, Ohio 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, Ohio | Statement: [Zapp, locationOfFormation, Dayton, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dayton, Ohio
Context triple: [Zapp, locationOfFormation, Dayton, Ohio]
  • 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. Dayton
    Dayton is a masculine given name of English origin used both as a first name and a surname.
  • D. Dayton
    Dayton is a small city in Minnesota known for its suburban-rural character and location within the Minneapolis–Saint Paul metropolitan area.
  • E. Dayton
    Dayton is a small town located in the state of Indiana in the United States.
  • 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ebce4f48190ba282ecb4fb2f6fa completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56b6f3dc81909a97913da6b739bd completed May 9, 2026, 3:45 p.m.
Created at: April 10, 2026, 3:20 a.m.