Triple

T20318928
Position Surface form Disambiguated ID Type / Status
Subject Dan Mullen E492155 entity
Predicate name P16 FINISHED
Object Dan Mullen 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: Dan Mullen | Statement: [Dan Mullen, name, Dan Mullen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Mullen
Context triple: [Dan Mullen, name, Dan Mullen]
  • A. Dan Mullen chosen
    Dan Mullen is an American college football coach best known for his successful tenures as head coach at Mississippi State and the University of Florida, where he developed several prominent quarterbacks.
  • B. Ed Orgeron
    Ed Orgeron is an American football coach best known for leading the LSU Tigers to a national championship during the 2019 season.
  • C. Jimbo Fisher
    Jimbo Fisher is an American college football coach best known for leading Florida State to a national championship and later serving as head coach of the Texas A&M Aggies.
  • D. Lane Kiffin
    Lane Kiffin is an American football coach known for his high-powered offensive schemes and headline-grabbing tenures at major college programs and in the NFL.
  • E. Leon Dabo
    Leon Dabo was an American painter best known for his atmospheric, subtly colored landscapes and cityscapes that exemplify the Tonalist movement in the late 19th and early 20th centuries.
  • 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_69e0b4a0134081909113563e1c3ba68a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67789d8108190ae2e134f4b0b0be5 completed April 20, 2026, 6:59 p.m.
Created at: April 16, 2026, 11:20 a.m.