Triple

T16771841
Position Surface form Disambiguated ID Type / Status
Subject John Henry Patterson E407615 entity
Predicate residence P75 FINISHED
Object Dayton, Ohio E1190566 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: [John Henry Patterson, residence, Dayton, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dayton, Ohio
Context triple: [John Henry Patterson, residence, Dayton, Ohio]
  • A. Dayton, Ohio chosen
    Dayton, Ohio is a mid-sized city in southwestern Ohio known as a historic center of aviation innovation and manufacturing.
  • B. Dayton
    Dayton is a small town located in the state of Indiana in the United States.
  • C. Dayton
    Dayton is an unincorporated community and census-designated place located within South Brunswick Township in Middlesex County, New Jersey.
  • D. 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.
  • E. Dayton
    Dayton is a masculine given name of English origin used both as a first name and a surname.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b036ff788190bd9f166c3f127818 completed April 18, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d45013048190a8073f34820ca85a completed May 10, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:21 a.m.