Triple

T6247558
Position Surface form Disambiguated ID Type / Status
Subject Bud Selig E139756 entity
Predicate spouse P13 FINISHED
Object Sue Selig E139756 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: Sue Selig | Statement: [Bud Selig, spouse, Sue Selig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sue Selig
Context triple: [Bud Selig, spouse, Sue Selig]
  • A. Sue Selig chosen
    Sue Selig is the wife of former Major League Baseball commissioner Bud Selig and is known for her involvement in charitable and community activities.
  • B. Nancy Lieberman
    Nancy Lieberman is a pioneering American basketball player and coach, widely regarded as one of the greatest figures in women's basketball history and a trailblazer for women in the sport.
  • C. Sue Gunter
    Sue Gunter was a Hall of Fame American women’s basketball coach best known for her long, successful tenure leading major collegiate programs and elevating the profile of the women’s game.
  • D. Laurie Cahn
    Laurie Cahn is a child of the famed American songwriter and lyricist Sammy Cahn.
  • E. Gail Berman
    Gail Berman is an American television and film producer and media executive known for her influential roles at major studios and for producing high-profile projects across network TV and Hollywood.
  • 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_69c008b1c5088190ae6de2555fc05ad8 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0631f511c81908d413320efdce42e completed March 22, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5191599d0819098a1b20b9d680f4b completed March 26, 2026, 11:31 a.m.
Created at: March 22, 2026, 4:23 p.m.