Triple

T2482436
Position Surface form Disambiguated ID Type / Status
Subject Sharpsburg, Georgia E55848 entity
Predicate county P75 FINISHED
Object Coweta County E105252 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: Coweta County | Statement: [Sharpsburg, Georgia, county, Coweta County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Coweta County
Context triple: [Sharpsburg, Georgia, county, Coweta County]
  • A. Coweta County chosen
    Coweta County is a county in west-central Georgia, part of the Atlanta metropolitan area, known for its historic communities and growing suburban population.
  • B. Cole County
    Cole County was the former name of what is now Union County in the southeastern part of South Dakota.
  • C. Cleveland County
    Cleveland County is a county in southwestern North Carolina that forms part of the greater Charlotte metropolitan region.
  • D. Lea County
    Lea County is a largely rural, oil- and gas-producing county in southeastern New Mexico known for its energy industry and agricultural activities.
  • E. Johnson County
    Johnson County is a county in eastern Iowa that includes Iowa City, home to the University of Iowa and a major regional center for education and healthcare.
  • 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_69ab49e670a88190b928e08302381710 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd163378481908b75f2f5de0e89c6 completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17b48d0881909442717d318a6f05 completed March 9, 2026, 6:55 p.m.
Created at: March 6, 2026, 9:45 p.m.