Triple

T15047230
Position Surface form Disambiguated ID Type / Status
Subject Madison Metro E379260 entity
Predicate alsoServes P6337 FINISHED
Object Maple Bluff, Wisconsin E1028275 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: Maple Bluff, Wisconsin | Statement: [Madison Metro, alsoServes, Maple Bluff, Wisconsin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maple Bluff, Wisconsin
Context triple: [Madison Metro, alsoServes, Maple Bluff, Wisconsin]
  • A. Maple Bluff, Wisconsin chosen
    Maple Bluff, Wisconsin is a small, affluent village near Madison best known as the home of the Wisconsin Governor's Mansion.
  • B. Waubeka, Wisconsin
    Waubeka, Wisconsin is an unincorporated community in Ozaukee County known as the birthplace of Flag Day in the United States.
  • C. Bloomer, Wisconsin
    Bloomer, Wisconsin is a small city in northwestern Wisconsin known for its rural community character and local agricultural roots.
  • D. Clearfield, Wisconsin
    Clearfield, Wisconsin is a small unincorporated community located within Juneau County in the central part of the state.
  • E. St. Germain, Wisconsin
    St. Germain, Wisconsin is a small Northwoods town known for its lakes, outdoor recreation, and tourism in northern 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69deda8e64e48190873104a02a676ff3 completed April 15, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9de73614819098b7a88624407d0e completed May 9, 2026, 2:37 a.m.
Created at: April 10, 2026, 3 a.m.