Triple

T4710885
Position Surface form Disambiguated ID Type / Status
Subject Jeffrey Sprecher E104506 entity
Predicate placeOfBirth P1 FINISHED
Object Madison, Wisconsin E11896 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: Madison, Wisconsin | Statement: [Jeffrey Sprecher, placeOfBirth, Madison, Wisconsin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madison, Wisconsin
Context triple: [Jeffrey Sprecher, placeOfBirth, Madison, Wisconsin]
  • A. Madison, Wisconsin, United States chosen
    Madison, Wisconsin, United States is the capital city of Wisconsin, known for its major research university, vibrant cultural scene, and numerous lakes.
  • B. Madison
    Madison is a suburban city in northern Alabama known for its proximity to Huntsville and its strong schools and residential communities.
  • C. Madison
    Madison is a coastal town in south-central Connecticut known for its beaches, historic New England charm, and popular Hammonasset Beach State Park.
  • D. Madison
    Madison is a common English surname and given name, historically associated with U.S. President James Madison and now widely used as a first name, especially for girls.
  • E. Madison
    Madison is the capital city of Wisconsin, known for its lakes, vibrant university community, and progressive culture.
  • 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_69bd43eac3c08190af7e4020c6c3704c completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd63ee712c81908da60aa0df58efe0 completed March 20, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67bb17e0819099a6d4f3ca54f616 completed March 21, 2026, 9:41 a.m.
Created at: March 20, 2026, 1:17 p.m.