Triple

T4677066
Position Surface form Disambiguated ID Type / Status
Subject McIntosh County, Georgia E103706 entity
Predicate contains P35 FINISHED
Object Darien, Georgia E377640 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: Darien, Georgia | Statement: [McIntosh County, Georgia, contains, Darien, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Darien, Georgia
Context triple: [McIntosh County, Georgia, contains, Darien, Georgia]
  • A. Darien, Georgia chosen
    Darien, Georgia is a historic coastal city in McIntosh County known for its shrimping industry and scenic marshlands along the Atlantic coast.
  • B. Vidette, Georgia
    Vidette, Georgia is a small unincorporated rural community located in Burke County in the eastern part of the state.
  • C. Folkston, Georgia
    Folkston, Georgia is a small city in southeastern Georgia known as a gateway to the Okefenokee Swamp and a popular spot for train watching.
  • D. Union Point, Georgia
    Union Point, Georgia is a small historic city in Greene County known for its railroad heritage and preserved 19th-century architecture.
  • E. De Soto, Georgia
    De Soto, Georgia is a small rural city located in southwestern Georgia 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_69bd43dda32c8190938b37744ca270fc completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd63698a548190831863adddd32f31 completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4399ded08190ba97c9c2f98395ec completed March 21, 2026, 7:07 a.m.
Created at: March 20, 2026, 1:16 p.m.