Triple

T1316066
Position Surface form Disambiguated ID Type / Status
Subject Chambers County, Alabama E28104 entity
Predicate hasSettlement P1068 FINISHED
Object Cusseta, Alabama E295814 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: Cusseta, Alabama | Statement: [Chambers County, Alabama, hasSettlement, Cusseta, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cusseta, Alabama
Context triple: [Chambers County, Alabama, hasSettlement, Cusseta, Alabama]
  • A. Cusseta, Alabama chosen
    Cusseta, Alabama is a small rural town in eastern Alabama known for its quiet community within Chambers County.
  • B. Atmore, Alabama
    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.
  • C. Lanett, Alabama
    Lanett, Alabama is a small city in eastern Alabama near the Georgia border, historically tied to the textile industry and the Chattahoochee River region.
  • D. 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.
  • E. 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.
  • 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_69a498532c3481909223b74af2e578df completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c173a72481909a820d6da6ef9e69 completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b030cd78548190a07264d42e18906b completed March 10, 2026, 2:55 p.m.
Created at: March 1, 2026, 7:55 p.m.