Triple

T22271925
Position Surface form Disambiguated ID Type / Status
Subject GONZ E550498 entity
Predicate associatedWith P37 FINISHED
Object Mark Few NE NERFINISHED

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: Mark Few | Statement: [GONZ, associatedWith, Mark Few]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark Few
Context triple: [GONZ, associatedWith, Mark Few]
  • A. Mark Few chosen
    Mark Few is a highly successful American college basketball coach best known for turning Gonzaga University into a perennial national powerhouse and NCAA Tournament contender.
  • B. Mark Turgeon
    Mark Turgeon is an American college basketball coach best known for leading the University of Maryland men's basketball program through much of the 2010s and early 2020s.
  • C. Scott Dabo
    Scott Dabo was an American painter active in the late 19th and early 20th centuries, known for his atmospheric landscapes and association with the Tonalist movement.
  • D. Frank Haith
    Frank Haith is an American college basketball coach best known for leading programs such as the Miami Hurricanes, Missouri Tigers, and Tulsa Golden Hurricane men's teams.
  • E. Brad Brownell
    Brad Brownell is an American college basketball coach best known for leading the Clemson Tigers men’s basketball program.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e43d8208190aff4f9cf7f2c2a8a completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f14ea449648190bb89ca292d32f59d completed April 29, 2026, 12:19 a.m.
Created at: April 16, 2026, 8:40 p.m.