Triple

T23734580
Position Surface form Disambiguated ID Type / Status
Subject Ben Askren E586504 entity
Predicate turnedProfessionalInMMA P65311 FINISHED
Object 2009 LITERAL 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: 2009 | Statement: [Ben Askren, turnedProfessionalInMMA, 2009]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: turnedProfessionalInMMA
Context triple: [Ben Askren, turnedProfessionalInMMA, 2009]
  • A. turnedProfessionalInBodybuilding
    Indicates that a person began their career as a professional in the sport of bodybuilding at a specified time or event.
  • B. professionalMMAStartYear chosen
    Indicates the calendar year in which an individual began competing in professional mixed martial arts.
  • C. roleInMMAHistory
    Indicates the specific part or significance an entity has played in the development, events, or legacy of mixed martial arts history.
  • D. transitionedToProfessionalStatusAs
    Indicates that an entity changed from a non-professional state or role into a professional status specifically in relation to another entity.
  • E. yearsActiveInMMA
    Indicates the span of time, in years, during which an entity has been actively involved in mixed martial arts competition or participation.
  • F. None of above.

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_69e24907dc9c8190be074c9c96a0ec2d completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1bacfb3d0819085a11140ac7aeb12 completed April 29, 2026, 8:01 a.m.
PD Predicate disambiguation batch_69f155f012808190a4b1cbc155558ade completed April 29, 2026, 12:50 a.m.
Created at: April 17, 2026, 7:10 p.m.