Triple
T7645168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mickey Mouse Funhouse |
E173100
|
entity |
| Predicate | hasEducationalElements |
P40345
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mickey Mouse Funhouse, hasEducationalElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationalElements Context triple: [Mickey Mouse Funhouse, hasEducationalElements, true]
-
A.
hasEducationalFeature
chosen
Indicates that something includes or is associated with a component, characteristic, or functionality intended for educational purposes.
-
B.
hasEducationalMaterial
Indicates that an entity provides, contains, or is associated with educational content or learning resources for another entity.
-
C.
hasEducationalLink
Indicates that there is an educational relationship or connection between two entities, such as teaching, learning, training, or academic affiliation.
-
D.
hasEducationalUse
Indicates that something is intended to be used for educational or instructional purposes.
-
E.
hasEducationalAudience
Indicates that something is intended for or directed toward a specific educational audience or learner group.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faf2aa1c8190945a691e46300ef2 |
completed | March 27, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e9ef1c81909c8bff716541ac1f |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:58 p.m.