Triple

T16420609
Position Surface form Disambiguated ID Type / Status
Subject Fox Cities E398807 entity
Predicate hasCity P316 FINISHED
Object Kimberly, Wisconsin E1118423 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: Kimberly, Wisconsin | Statement: [Fox Cities, hasCity, Kimberly, Wisconsin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kimberly, Wisconsin
Context triple: [Fox Cities, hasCity, Kimberly, Wisconsin]
  • A. Kimberly, Wisconsin chosen
    Kimberly, Wisconsin is a small village in Outagamie County known historically as a paper mill community along the Fox River in northeastern Wisconsin.
  • B. Kimball, Wisconsin
    Kimball, Wisconsin is an unincorporated community located in Iron County in the northern part of the state.
  • C. Wilmot, Wisconsin
    Wilmot, Wisconsin is a small unincorporated community in Kenosha County known for its proximity to the Wilmot Mountain ski and snowboard area.
  • D. Knight, Wisconsin
    Knight, Wisconsin is a small unincorporated community located in Iron County in the northern part of the state.
  • E. Kingston, Wisconsin
    Kingston, Wisconsin is a small rural village in Green Lake County known for its quiet community and location along key regional routes in central Wisconsin.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328f735b08190aec8331f54817462 completed April 18, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00581245108190842cfd68ec640236 completed May 10, 2026, 10:04 a.m.
Created at: April 10, 2026, 5:09 a.m.