Triple

T4629843
Position Surface form Disambiguated ID Type / Status
Subject Toronto Marlboros E101385 entity
Predicate notableAlumni P51 FINISHED
Object Dave Keon E393148 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: Dave Keon | Statement: [Toronto Marlboros, notableAlumni, Dave Keon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dave Keon
Context triple: [Toronto Marlboros, notableAlumni, Dave Keon]
  • A. Dave Keon chosen
    Dave Keon is a Hall of Fame Canadian ice hockey centre best known as a longtime Toronto Maple Leafs star and one of the franchise’s greatest two-way players.
  • B. Dave Keuning
    Dave Keuning is an American guitarist and songwriter best known as the lead guitarist and a founding member of the rock band The Killers.
  • C. Scott Kevan
    Scott Kevan is a cinematographer known for his work on feature films, including the science fiction horror movie "The Darkest Hour."
  • D. Stephen Koepp
    Stephen Koepp is an American journalist and editor best known as a longtime senior editor at Time magazine and co-founder of the business news site "From Day One."
  • E. Mike Krieger
    Mike Krieger is a Brazilian-American entrepreneur and software engineer best known as the co-founder and former CTO of the photo-sharing social media platform Instagram.
  • 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_69bd43d2f1c081908cd4b7ec48ecc73d completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a316ef48190831970ec914cf5a2 completed March 20, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfab992148190a1b1dfa33b971d11 completed March 21, 2026, 1:56 a.m.
Created at: March 20, 2026, 1:13 p.m.