Triple

T1797060
Position Surface form Disambiguated ID Type / Status
Subject Mathematical Magic Show E39627 entity
Predicate educationalValue P10669 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 Magic Show, educationalValue, introduces mathematical concepts through puzzles]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: educationalValue
Context triple: [Mathematical Magic Show, educationalValue, introduces mathematical concepts through puzzles]
  • A. educationalImpact chosen
    Indicates the effect or influence that one entity has on the learning, knowledge, or educational outcomes of another.
  • B. educates
    Indicates that one entity provides instruction, knowledge, or training to another entity.
  • C. educationalFocus
    Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
  • D. educationalApproach
    Indicates the method, strategy, or philosophy used to guide teaching and learning within an educational context.
  • 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_69a88632aa588190ba3978fde0db5bbd completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69ab61b6ea188190aab9fb839bf1e367 completed March 6, 2026, 11:22 p.m.
PD Predicate disambiguation batch_69aa61d2f7a8819090301f92d3e358c7 completed March 6, 2026, 5:10 a.m.
Created at: March 4, 2026, 7:32 p.m.