Triple

T20467283
Position Surface form Disambiguated ID Type / Status
Subject Fox (Wanted character) E502084 entity
Predicate mentorOf P7251 FINISHED
Object Wesley Gibson 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: Wesley Gibson | Statement: [Fox (Wanted character), mentorOf, Wesley Gibson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wesley Gibson
Context triple: [Fox (Wanted character), mentorOf, Wesley Gibson]
  • A. Wesley Gibson chosen
    Wesley Gibson is the downtrodden office worker-turned-assassin protagonist of the action film "Wanted," who discovers he is heir to a secret fraternity of killers.
  • B. Wesley Dennis
    Wesley Dennis was an American illustrator best known for his expressive drawings of horses in classic children's books.
  • C. Wesley Bishop
    Wesley Bishop is a notable individual who shares the surname Bishop and has achieved sufficient recognition to be specifically identified among people with that name.
  • D. Wesley Saunders
    Wesley Saunders is an American basketball player best known for starring as a versatile guard/forward for Harvard University, where he became one of the program’s top performers in the early 2010s.
  • E. Blaine Gibson
    Blaine Gibson was an American animator and sculptor best known for his long career at Disney, where he created many of the iconic Audio-Animatronic figures for Disneyland and other Disney parks.
  • 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_69e0b4ae5f1081908768b0c9a3a0bf38 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6995d9d1c81909ee223a35a0850ba completed April 20, 2026, 9:23 p.m.
Created at: April 16, 2026, 11:33 a.m.