Triple

T2343321
Position Surface form Disambiguated ID Type / Status
Subject Peach County E45074 entity
Predicate hasCountySeat P383 FINISHED
Object Fort Valley E48346 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: Fort Valley | Statement: [Peach County, hasCountySeat, Fort Valley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fort Valley
Context triple: [Peach County, hasCountySeat, Fort Valley]
  • A. Fort Valley, Georgia chosen
    Fort Valley, Georgia is a small city in central Georgia known as the home of Fort Valley State University and a hub for the state’s peach-growing industry.
  • B. Dawsonville
    Dawsonville is a small city in north Georgia known for its gold rush history and strong ties to stock car racing and NASCAR culture.
  • C. Mauldin
    Mauldin is a city in South Carolina, United States, known as a suburban community within the Greenville metropolitan area.
  • D. Fort Payne
    Fort Payne is a small city in northeastern Alabama known for its scenic Appalachian setting and historic role in the Cherokee Nation and the Trail of Tears.
  • E. Woodfin
    Woodfin is the surname of Randall Woodfin, an American politician and mayor of Birmingham, Alabama.
  • 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_69a88917935081909b755dbf38e81024 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abc6ae33e881909a81a0c0def59059 completed March 7, 2026, 6:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae96253f0c81908b866c656c3f5bea completed March 9, 2026, 9:43 a.m.
Created at: March 4, 2026, 7:52 p.m.