Triple

T35115066
Position Surface form Disambiguated ID Type / Status
Subject Christopher d'Amboise E1013409 entity
Predicate hasProfessionalTrainingIn P96696 FINISHED
Object classical ballet 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: classical ballet | Statement: [Christopher d'Amboise, hasProfessionalTrainingIn, classical ballet]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasProfessionalTrainingIn
Context triple: [Christopher d'Amboise, hasProfessionalTrainingIn, classical ballet]
  • A. hasHandsOnTraining
    Indicates that an entity has received practical, experiential instruction or practice in performing a specific task or activity.
  • B. trainedAs
    Indicates that one entity has received education or instruction to perform the role, profession, or function represented by another entity.
  • C. receivedTrainingIn chosen
    Indicates that one entity has undergone or been provided with training or instruction in a particular field, skill, or subject associated with another entity.
  • D. hasTrainingFor
    Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
  • E. hasTrainingRole
    Indicates that an entity holds or is assigned a specific role within a training or instructional context.
  • 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_69f76dd659d08190bcdc00d37caafb62 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_6a035ac41d088190b7e76b93c1410090 completed May 12, 2026, 4:52 p.m.
PD Predicate disambiguation batch_6a035a4f290c8190a0101295a38ae8b8 completed May 12, 2026, 4:50 p.m.
Created at: May 3, 2026, 4:01 p.m.