Triple
T20089948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al Akhawayn University in Ifrane |
E496241
|
entity |
| Predicate | hasInstructionModel |
P138677
|
FINISHED |
| Object | American credit-hour system |
—
|
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: American credit-hour system | Statement: [Al Akhawayn University in Ifrane, hasInstructionModel, American credit-hour system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInstructionModel Context triple: [Al Akhawayn University in Ifrane, hasInstructionModel, American credit-hour system]
-
A.
hasStudyModel
Indicates that an entity is associated with, or defined by, a particular study model used for analysis, simulation, or representation.
-
B.
hasModelStatus
Indicates that an entity is assigned a particular model-related state or condition, such as its current phase, validity, or operational status within a modeling context.
-
C.
hasModelLine
Indicates that an item, product, or entity belongs to or is associated with a particular model line or series.
-
D.
hasNavigationModel
Indicates that an entity is associated with or uses a specific navigation model that defines how it determines or follows routes or paths.
-
E.
hasModelOccupation
Indicates that an entity’s occupation or job role is that of a model.
- F. None of above. chosen
Provenance (4 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6655e1ef0819095f40a1ce2eb17b7 |
completed | April 20, 2026, 5:41 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 11:20 p.m.