Triple

T11132426
Position Surface form Disambiguated ID Type / Status
Subject Grand River E263317 entity
Predicate crosses P416 FINISHED
Object Brant County E422766 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: Brant County | Statement: [Grand River, crosses, Brant County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brant County
Context triple: [Grand River, crosses, Brant County]
  • A. Brant County chosen
    Brant County is a predominantly rural municipality in southwestern Ontario, Canada, known for its agricultural communities and proximity to the Six Nations of the Grand River reserve.
  • B. Evans County
    Evans County is a rural county in southeastern Georgia known for its agricultural landscape and small-town communities.
  • C. Kelan County
    Kelan County is a county in Xinzhou, Shanxi Province, China, known for its proximity to the Taiyuan Satellite Launch Center, one of the country’s major space launch facilities.
  • D. Blount County
    Blount County is a county in eastern Tennessee known for encompassing part of the Great Smoky Mountains and serving as a suburban and recreational area near Knoxville.
  • E. Blount County
    Blount County is a county in north-central Alabama known for its rural communities, scenic landscapes, and historic covered bridges.
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8347a248190837e8c26f25f553a completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e441e6b72881908f8288e99df0cb7c completed April 19, 2026, 2:45 a.m.
Created at: April 8, 2026, 9:28 p.m.