Triple

T1857124
Position Surface form Disambiguated ID Type / Status
Subject Escambia County, Alabama E41727 entity
Predicate hasSettlement P1068 FINISHED
Object Atmore, Alabama E209148 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: Atmore, Alabama | Statement: [Escambia County, Alabama, hasSettlement, Atmore, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Atmore, Alabama
Context triple: [Escambia County, Alabama, hasSettlement, Atmore, Alabama]
  • A. Atmore, Alabama chosen
    Atmore, Alabama is a small city in Escambia County near the Florida state line, known historically for its railroad roots and proximity to several state and federal correctional facilities.
  • B. Saraland
    Saraland is a suburban city in Mobile County, Alabama, known as part of the Mobile metropolitan area and for its residential communities and local industry.
  • C. Moody, Alabama
    Moody, Alabama is a small suburban city in central Alabama that forms part of the Birmingham metropolitan area.
  • D. Orange Beach
    Orange Beach is a coastal resort city on Alabama’s Gulf Coast known for its white-sand beaches, boating, and vacation attractions.
  • E. Opelika
    Opelika is a city in eastern Alabama known for its proximity to Auburn and its role as a regional center for industry and commerce.
  • 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_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb07fc5f08190a195a2f24d7b858a completed March 7, 2026, 4:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3c82d50819094e8ccdba0faf819 completed March 8, 2026, 10:10 p.m.
Created at: March 4, 2026, 7:33 p.m.