Triple

T6478604
Position Surface form Disambiguated ID Type / Status
Subject Above the Rim E146132 entity
Predicate starring P1507 FINISHED
Object Tonya Pinkins E579196 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: Tonya Pinkins | Statement: [Above the Rim, starring, Tonya Pinkins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tonya Pinkins
Context triple: [Above the Rim, starring, Tonya Pinkins]
  • A. Tonya Pinkins chosen
    Tonya Pinkins is a Tony Award–winning American actress and singer known for her powerful performances on Broadway, in film, and on television.
  • B. Teresa Weatherspoon
    Teresa Weatherspoon is a Hall of Fame American basketball player and coach best known as an original WNBA star and defensive standout at point guard.
  • C. Jennifer Azzi
    Jennifer Azzi is a former American basketball star and Olympic gold medalist who led Stanford University to an NCAA championship before playing professionally and later becoming a coach and sports executive.
  • D. Linda Oubre
    Linda Oubre is an American academic leader and administrator who serves as the president of Whittier College.
  • E. Cheryl Miller
    Cheryl Miller is a legendary American basketball player and coach widely regarded as one of the greatest women’s players in history.
  • 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_69c008fec7408190af7b146dc63d9750 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a4d35f08190a94143367b1d45c5 completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c653aa82808190a1e9d420e81d7839 completed March 27, 2026, 9:53 a.m.
Created at: March 22, 2026, 4:51 p.m.