Triple

T3616616
Position Surface form Disambiguated ID Type / Status
Subject Altamaha River E76615 entity
Predicate hasMouthNear P350 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: [Altamaha River, hasMouthNear, Darien, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Darien, Georgia
Context triple: [Altamaha River, hasMouthNear, 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. Union Point, Georgia
    Union Point, Georgia is a small historic city in Greene County known for its railroad heritage and preserved 19th-century architecture.
  • D. De Soto, Georgia
    De Soto, Georgia is a small rural city located in southwestern Georgia in the United States.
  • E. Bainbridge, Georgia
    Bainbridge, Georgia is a small city in the southwestern part of the state known for its outdoor recreation, historic downtown, and proximity to major waterways near the Florida border.
  • 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_69ad85dae2fc81908d1ceadbc6af0089 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc27c98088190a493c9eddf6b206a completed March 8, 2026, 6:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3852e60819092db2992e945a4c7 completed March 14, 2026, 2:10 a.m.
Created at: March 8, 2026, 3:23 p.m.