Triple

T15047217
Position Surface form Disambiguated ID Type / Status
Subject Madison Metro E379260 entity
Predicate operatedBy P86 FINISHED
Object City of Madison E369510 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: City of Madison | Statement: [Madison Metro, operatedBy, City of Madison]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Madison
Context triple: [Madison Metro, operatedBy, City of Madison]
  • A. City of Madison chosen
    The City of Madison is the capital of Wisconsin, known for its lakeside setting, major public university, and vibrant civic and cultural life.
  • B. Fort Madison
    Fort Madison is a historic riverfront city in southeastern Iowa known for its Mississippi River port, 19th-century military fort heritage, and role as a regional transportation hub.
  • C. City of Wauwatosa
    The City of Wauwatosa is a suburban municipality in southeastern Wisconsin known for its residential neighborhoods, commercial districts, and proximity to Milwaukee.
  • D. Racine
    Racine is a small city located in southeastern Minnesota in the United States.
  • E. Racine
    Racine is a city in southeastern Wisconsin located on the shore of Lake Michigan, known historically for its manufacturing industry and Danish kringle pastries.
  • 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_69ff56b25a808190b56f8ab3c506b771 completed May 9, 2026, 3:45 p.m.
Created at: April 10, 2026, 3 a.m.