Triple
T12043916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Phoenix |
E286734
|
entity |
| Predicate | primaryModeOfInstruction |
P1302
|
FINISHED |
| Object | online |
—
|
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: online | Statement: [University of Phoenix, primaryModeOfInstruction, online]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryModeOfInstruction Context triple: [University of Phoenix, primaryModeOfInstruction, online]
-
A.
primaryLanguageOfInstruction
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
B.
typeOfTeaching
Indicates the specific method or style of teaching used in an instructional context.
-
C.
mediumOfInstruction
Indicates that a particular language or medium is used as the primary means of instruction or teaching in an educational context.
-
D.
primaryProgram
Indicates that one entity serves as the main or principal program associated with another entity, distinguishing it from any secondary or auxiliary programs.
-
E.
primaryMode
chosen
Indicates the main or most commonly used method, manner, or form in which an action, process, or interaction is carried out between entities.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bac9e08190aa1a99c835f29542 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:47 p.m.