Triple

T13268996
Position Surface form Disambiguated ID Type / Status
Subject Léo-Guy Morrissette E316003 entity
Predicate sportBusinessInvolvement P17882 FINISHED
Object ice hockey 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: ice hockey | Statement: [Léo-Guy Morrissette, sportBusinessInvolvement, ice hockey]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: sportBusinessInvolvement
Context triple: [Léo-Guy Morrissette, sportBusinessInvolvement, ice hockey]
  • A. sportIndustry
    Indicates a relationship where an entity is involved in, associated with, or part of the sports industry or sports-related economic sector.
  • B. sportsBusinessRole
    Indicates a professional role or position that an entity holds within the context of sports business or the sports industry.
  • C. sportsInfluence
    Indicates a relationship where one entity affects, shapes, or contributes to another entity’s involvement, performance, or outcomes in sports.
  • D. otherSportIndustry
    Indicates a relationship where an entity is involved in, associated with, or belongs to a sports-related industry other than the primary or specified one.
  • E. sportsInvolvement chosen
    Indicates the nature or extent of an entity’s participation in, association with, or role within a sport or sporting activity.
  • 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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99cfdc9388190af1fdd3cd4717bd8 completed April 11, 2026, 12:59 a.m.
PD Predicate disambiguation batch_69d98f60911081909fa346a054f76c9f completed April 11, 2026, 12:01 a.m.
Created at: April 9, 2026, 9:26 p.m.