Triple

T5213018
Position Surface form Disambiguated ID Type / Status
Subject Moraine, Ohio E117678 entity
Predicate locatedNear P294 FINISHED
Object Dayton, Ohio E152840 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: [Moraine, Ohio, locatedNear, Dayton, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dayton, Ohio
Context triple: [Moraine, Ohio, locatedNear, 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
    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, Ohio, United States chosen
    Dayton is a mid-sized city in southwestern Ohio known historically as a center of aviation innovation and manufacturing.
  • 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_69bd4464ba3c8190bc16b2ebbe42ddb0 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a730e6c8190ae6082da41ee592a completed March 20, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c059bd73e481909e23e1796262b8c4 completed March 22, 2026, 9:06 p.m.
Created at: March 20, 2026, 1:47 p.m.