Triple

T14986066
Position Surface form Disambiguated ID Type / Status
Subject Bonifay K-8 School E373702 entity
Predicate city P40 FINISHED
Object Bonifay E76756 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: Bonifay | Statement: [Bonifay K-8 School, city, Bonifay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bonifay
Context triple: [Bonifay K-8 School, city, Bonifay]
  • A. Bonifay, Florida chosen
    Bonifay, Florida is a small city in the Florida Panhandle known as the administrative and commercial hub of Holmes County.
  • B. Tallassee
    Tallassee is a small city in central Alabama known for its location along the Tallapoosa River and its historic textile mill heritage.
  • C. Griffins Bend
    Griffins Bend is a well-known high-speed corner on Australia’s Mount Panorama motor racing circuit, challenging drivers with its steep uphill approach and limited visibility.
  • D. Tullahassee
    Tullahassee is a small historic town in eastern Oklahoma known as one of the oldest surviving all-Black towns in the United States.
  • E. Waynoka
    Waynoka is a small city in northwestern Oklahoma known historically as a railroad hub and as a gateway to the nearby Little Sahara State Park sand dunes.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7007588819095bb1de029a6f2eb completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69feae0652dc8190a90a1c3b07a6ed94 completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 2:52 a.m.