Triple

T12863390
Position Surface form Disambiguated ID Type / Status
Subject Hinds County, Mississippi E307652 entity
Predicate contains P35 FINISHED
Object Byram, Mississippi E348932 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: Byram, Mississippi | Statement: [Hinds County, Mississippi, contains, Byram, Mississippi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Byram, Mississippi
Context triple: [Hinds County, Mississippi, contains, Byram, Mississippi]
  • A. Byram, Mississippi chosen
    Byram, Mississippi is a small suburban city in central Mississippi that serves as part of the Jackson metropolitan area.
  • B. Byhalia, Mississippi
    Byhalia, Mississippi is a small town in northern Mississippi known for its rural character and proximity to the Memphis metropolitan area.
  • C. Bailey, Mississippi
    Bailey, Mississippi is a small unincorporated rural community located in Lauderdale County in the eastern part of the state.
  • D. Benoit, Mississippi
    Benoit, Mississippi is a small town in Bolivar County best known for its historic antebellum homes and as a filming location for classic Southern-set movies.
  • E. Winona, Mississippi
    Winona, Mississippi is a small city in central Mississippi known as a local commercial and transportation hub along Interstate 55.
  • 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_69d7bdf5e7cc8190be357278bc5ba3bb completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9708cf6b48190886a99e04d85d348 completed April 10, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd46686c288190a51847f86785568a completed May 8, 2026, 2:11 a.m.
Created at: April 9, 2026, 5:37 p.m.