Triple

T1924038
Position Surface form Disambiguated ID Type / Status
Subject Mathematical Circus E40187 entity
Predicate educationalAspect P779 FINISHED
Object introduces mathematical concepts through puzzles 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: introduces mathematical concepts through puzzles | Statement: [Mathematical Circus, educationalAspect, introduces mathematical concepts through puzzles]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: educationalAspect
Context triple: [Mathematical Circus, educationalAspect, introduces mathematical concepts through puzzles]
  • A. educationalFocus
    Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
  • B. educationalImpact
    Indicates the effect or influence that one entity has on the learning, knowledge, or educational outcomes of another.
  • C. educationalApproach chosen
    Indicates the method, strategy, or philosophy used to guide teaching and learning within an educational context.
  • D. educates
    Indicates that one entity provides instruction, knowledge, or training to another entity.
  • E. educationalModel
    Indicates that one entity serves as an educational model, framework, or paradigm that guides or structures the teaching, learning, or training practices of 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_69a8864298748190a2f2fd34f7ef8d77 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb2359ca0819082b514a34c469b21 completed March 7, 2026, 5:05 a.m.
PD Predicate disambiguation batch_69abafed2ab481908920334e77b1021b completed March 7, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:35 p.m.