Triple

T19517999
Position Surface form Disambiguated ID Type / Status
Subject Pike County, Alabama E488326 entity
Predicate hasCity P316 FINISHED
Object Brundidge, Alabama NE NERFINISHED

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: Brundidge, Alabama | Statement: [Pike County, Alabama, hasCity, Brundidge, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brundidge, Alabama
Context triple: [Pike County, Alabama, hasCity, Brundidge, Alabama]
  • A. Brundidge, Alabama chosen
    Brundidge, Alabama is a small city in southeastern Alabama known historically for its peanut butter production and rural community character.
  • B. Eldridge, Alabama
    Eldridge, Alabama is a small rural town located in Walker County in the northwestern part of the state.
  • C. Milstead, Alabama
    Milstead, Alabama is a small unincorporated rural community located in Macon County in the east-central part of the state.
  • D. Sylvania, Alabama
    Sylvania, Alabama is a small rural town in northeastern Alabama known for its close-knit community and location atop Sand Mountain.
  • E. Vredenburgh, Alabama
    Vredenburgh, Alabama is a small rural town located in Monroe County in the southern part of the state.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8da8bec819081f400199491ccc3 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6359da24c81909a0fd165a0fc0e33 completed April 20, 2026, 2:18 p.m.
Created at: April 10, 2026, 1:40 p.m.