Triple

T6107378
Position Surface form Disambiguated ID Type / Status
Subject Tyron Woodley E136148 entity
Predicate hasTrainedIn P22559 FINISHED
Object wrestling 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: wrestling | Statement: [Tyron Woodley, hasTrainedIn, wrestling]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTrainedIn
Context triple: [Tyron Woodley, hasTrainedIn, wrestling]
  • A. hasTrainingFor
    Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
  • B. trainedAs chosen
    Indicates that one entity has received education or instruction to perform the role, profession, or function represented by another entity.
  • C. hasTrained
    Indicates that one entity has provided training or instruction to another entity.
  • D. hasTrainingRole
    Indicates that an entity holds or is assigned a specific role within a training or instructional context.
  • E. trainingInstitution
    Indicates that one entity serves as the institution or organization where another entity receives training or education.
  • 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_69c0087dee9881909e3655be88208c01 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05b81fad081909b622cafc6d51249 completed March 22, 2026, 9:13 p.m.
PD Predicate disambiguation batch_69c049f80e2081909b7d84a104cda68d completed March 22, 2026, 7:58 p.m.
Created at: March 22, 2026, 4:13 p.m.