Triple

T390261
Position Surface form Disambiguated ID Type / Status
Subject Conn Smythe Trophy E8863 entity
Predicate namedPersonOccupation P12884 FINISHED
Object ice hockey executive 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 executive | Statement: [Conn Smythe Trophy, namedPersonOccupation, ice hockey executive]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: namedPersonOccupation
Context triple: [Conn Smythe Trophy, namedPersonOccupation, ice hockey executive]
  • A. namesakeOccupation
    Indicates that one entity’s occupation is the same as, or derived from, the occupation associated with the other entity’s namesake.
  • B. notablePersonnel
    Indicates that the subject has associated individuals who are particularly important, distinguished, or prominent in relation to it.
  • C. authorOccupation
    Indicates the professional role or job that an author holds or is associated with.
  • D. notableOfficeHolder
    Indicates that an entity is a significant or distinguished holder of a particular office or position associated with another entity.
  • E. notableCulturalFigure
    Indicates that a person holds significant influence or recognition within a culture’s arts, traditions, values, or public life.
  • F. None of above. chosen

Provenance (4 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_69a2e7f55c60819097aff65ea2ca2832 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec5bdc848190826701590070497b completed Feb. 28, 2026, 1:23 p.m.
PD Predicate disambiguation batch_69a2e96960608190bdd342da9c5ddb5e completed Feb. 28, 2026, 1:11 p.m.
PDg Predicate description generation batch_69a2ebac09408190be802b96bb203d5f completed Feb. 28, 2026, 1:20 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.