Triple

T36491689
Position Surface form Disambiguated ID Type / Status
Subject Relation Networks for few-shot learning E899065 entity
Predicate trainingMimics P20525 FINISHED
Object few-shot evaluation episodes 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: few-shot evaluation episodes | Statement: [Relation Networks for few-shot learning, trainingMimics, few-shot evaluation episodes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: trainingMimics
Context triple: [Relation Networks for few-shot learning, trainingMimics, few-shot evaluation episodes]
  • A. trainingModality
    Indicates the method or format through which training or instruction is delivered or conducted.
  • B. trainingUse chosen
    Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
  • C. trainerModel
    Indicates that one entity serves as the trainer or training source for a model entity.
  • D. trainingUnder
    Indicates that one entity is receiving instruction, guidance, or mentorship from another, typically in a subordinate or apprentice-like capacity.
  • E. trainingIn
    Indicates that one entity is undergoing or receiving training within the context, program, or domain specified by another entity.
  • 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_69f76e5ad4588190bdbce60c52fbb785 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c777e924819081a6634f549fe552 completed May 3, 2026, 10:08 p.m.
PD Predicate disambiguation batch_69f7c477a4d481908f52e55b6688f60c completed May 3, 2026, 9:56 p.m.
Created at: May 3, 2026, 4:10 p.m.