Triple
T902096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sports Illustrated for Kids |
E19468
|
entity |
| Predicate | hasEducationalAspect |
P12759
|
FINISHED |
| Object | promotes reading |
—
|
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: promotes reading | Statement: [Sports Illustrated for Kids, hasEducationalAspect, promotes reading]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationalAspect Context triple: [Sports Illustrated for Kids, hasEducationalAspect, promotes reading]
-
A.
hasEducationalAudience
Indicates that something is intended for or directed toward a specific educational audience or learner group.
-
B.
hasEducationalMission
Indicates that an entity is responsible for or engaged in carrying out an educational purpose, goal, or function.
-
C.
educationalImpact
Indicates the effect or influence that one entity has on the learning, knowledge, or educational outcomes of another.
-
D.
hasEducationalRole
Indicates that an entity holds a specific function, position, or responsibility within an educational context or setting.
-
E.
educationalActivity
chosen
Indicates an action or relationship in which one entity engages in or provides a learning or teaching activity for another.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad4412408190a6bf8fc7484a5781 |
completed | March 1, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69a4aa98caec8190bbcc38320090f058 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.