Triple

T21453633
Position Surface form Disambiguated ID Type / Status
Subject Brierfield, Alabama E529280 entity
Predicate near P350 FINISHED
Object Brent, 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: Brent, Alabama | Statement: [Brierfield, Alabama, near, Brent, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brent, Alabama
Context triple: [Brierfield, Alabama, near, Brent, Alabama]
  • A. Brent, Alabama chosen
    Brent, Alabama is a small city in central Alabama known for its rural character and location within Bibb County.
  • B. Bryant, Alabama
    Bryant, Alabama is an unincorporated community in Jackson County known for its rural character and proximity to the Tennessee state line within the Greater Chattanooga area.
  • C. Billingsley, Alabama
    Billingsley, Alabama is a small rural town in central Alabama known for its close-knit community and agricultural surroundings.
  • D. Benton, Alabama
    Benton, Alabama is a small rural town situated along the Alabama River in central Alabama.
  • E. Berry, Alabama
    Berry, Alabama is a small rural town in western Alabama known for its tight-knit community and location within Fayette County.
  • 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_69e0c457579481909db68053ed99750c completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9e9d50b88819081a771596d0a2b2b completed April 23, 2026, 9:43 a.m.
Created at: April 16, 2026, 6:07 p.m.