Triple

T577842
Position Surface form Disambiguated ID Type / Status
Subject Splash E13794 entity
Predicate leadCharacter P1668 FINISHED
Object Madison E61346 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 | Statement: [Splash, leadCharacter, Madison]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madison
Context triple: [Splash, leadCharacter, Madison]
  • A. Madison chosen
    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.
  • B. Madison, Wisconsin, United States
    Madison, Wisconsin, United States is the capital city of Wisconsin, known for its major research university, vibrant cultural scene, and numerous lakes.
  • C. Milwaukee
    Milwaukee is the largest city in Wisconsin, known for its brewing traditions, industrial history, and location on the western shore of Lake Michigan.
  • D. Green Bay, Wisconsin
    Green Bay, Wisconsin is a city in northeastern Wisconsin best known as the home of the NFL’s Green Bay Packers and one of the oldest continuously operating professional football franchises in the United States.
  • E. Jackson
    Jackson is a common English surname borne by numerous notable figures across politics, science, sports, and the arts.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b69fed88190b5558d4ebd5047a1 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a518c214088190963746dcb402b0b1 completed March 2, 2026, 4:57 a.m.
Created at: March 1, 2026, 7:33 p.m.