Triple

T9202886
Position Surface form Disambiguated ID Type / Status
Subject Tallapoosa County E220890 entity
Predicate countySeat P383 FINISHED
Object Dadeville E492284 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: Dadeville | Statement: [Tallapoosa County, countySeat, Dadeville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dadeville
Context triple: [Tallapoosa County, countySeat, Dadeville]
  • A. Dadeville, Alabama chosen
    Dadeville, Alabama is a small city in east-central Alabama that serves as a gateway to outdoor recreation areas, including the nearby Horseshoe Bend National Military Park and Lake Martin.
  • B. Branchton
    Branchton is a small locality known primarily for its railway station, which serves as a transport link for the surrounding area.
  • C. Temperanceville
    Temperanceville is a small community within the Township of King in Ontario, Canada, known for its rural character and historic roots.
  • D. Lynnville
    Lynnville is a small rural town located in central Iowa, United States.
  • E. Davie
    Davie is a diminutive or affectionate form of the given name David, commonly used in English-speaking contexts.
  • 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_69ca83e8e9248190862cf3e41693b310 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd944e6208190adfcc7f75197387d completed April 1, 2026, 8:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c4953588190aa842de269eee56c completed April 4, 2026, 12:33 a.m.
Created at: March 30, 2026, 7:26 p.m.