Triple

T15758180
Position Surface form Disambiguated ID Type / Status
Subject Ironwood, Michigan E382021 entity
Predicate borderedBy P224 FINISHED
Object Hurley, Wisconsin E972622 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: Hurley, Wisconsin | Statement: [Ironwood, Michigan, borderedBy, Hurley, Wisconsin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hurley, Wisconsin
Context triple: [Ironwood, Michigan, borderedBy, Hurley, Wisconsin]
  • A. Hurley, Wisconsin chosen
    Hurley, Wisconsin is a small city in northern Wisconsin known for its historic mining roots and location near the Upper Peninsula of Michigan.
  • B. Hatley, Wisconsin
    Hatley, Wisconsin is a small village in central Wisconsin known for its rural character and proximity to the Wausau metropolitan area.
  • C. Gurney, Wisconsin
    Gurney, Wisconsin is a small rural town located in Iron County in the northern part of the state.
  • D. Elkhorn, Wisconsin
    Elkhorn, Wisconsin is a small city in southeastern Wisconsin known as the administrative and commercial hub of Walworth County.
  • E. Houlton, Wisconsin
    Houlton, Wisconsin is a small unincorporated community in western Wisconsin near the St. Croix River, opposite Stillwater, Minnesota.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e050b35ea48190a758ee76a57b5451 completed April 16, 2026, 3 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff877311dc8190b55fe7ca5c0843da completed May 9, 2026, 7:13 p.m.
Created at: April 10, 2026, 4:47 a.m.