Triple

T11547540
Position Surface form Disambiguated ID Type / Status
Subject Kyrian E273808 entity
Predicate membershipProcess P45671 FINISHED
Object aspirant training 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: aspirant training | Statement: [Kyrian, membershipProcess, aspirant training]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: membershipProcess
Context triple: [Kyrian, membershipProcess, aspirant training]
  • A. membershipApplicationOf
    Indicates that one entity is a membership application that is submitted for or associated with another entity (typically the applicant or organization).
  • B. membershipFocus
    Indicates a relationship where the primary attention, priority, or emphasis is placed on the members of a group or organization, rather than on other aspects such as products, profits, or external stakeholders.
  • C. membershipCondition chosen
    Indicates the rule, requirement, or criterion that determines whether an entity qualifies for membership in a given group or set.
  • D. membershipField
    Indicates that one entity serves as a field or attribute capturing the membership status or association of another entity within a group, organization, or collection.
  • E. boardingProcess
    Indicates the process or sequence of actions by which passengers move from a waiting area onto a vehicle (such as an airplane, train, or bus).
  • 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_69d6aae4dfa48190a3ab0b19a159a3c5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d886e3ad548190b2c88332f5d919bd completed April 10, 2026, 5:13 a.m.
PD Predicate disambiguation batch_69d8087cbe7c819085680f3d67ccc978 completed April 9, 2026, 8:13 p.m.
Created at: April 8, 2026, 9:37 p.m.