Triple
T2225060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evening & Weekend MBA |
E48629
|
entity |
| Predicate | learningFormat |
P7876
|
FINISHED |
| Object | cohort-based in many schools |
—
|
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: cohort-based in many schools | Statement: [Evening & Weekend MBA, learningFormat, cohort-based in many schools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: learningFormat Context triple: [Evening & Weekend MBA, learningFormat, cohort-based in many schools]
-
A.
trainingFormat
Indicates the specific method or medium through which training is delivered or conducted.
-
B.
courseType
Indicates the classification or category of a course based on its nature, level, or instructional format.
-
C.
offersEducationMode
chosen
Indicates that an entity provides a particular mode or format in which education or instruction is delivered.
-
D.
courseShape
Indicates the geometric layout or configuration that defines the path or outline of a course.
-
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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03ec3788190b5ae32201364f7ab |
completed | March 7, 2026, 6:05 a.m. |
| PD | Predicate disambiguation | batch_69abbdac31d8819092d17815e11921e9 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.