Triple
T2225036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evening & Weekend MBA |
E48629
|
entity |
| Predicate | typicalStudentStatus |
P37157
|
FINISHED |
| Object | employed full-time |
—
|
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: employed full-time | Statement: [Evening & Weekend MBA, typicalStudentStatus, employed full-time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalStudentStatus Context triple: [Evening & Weekend MBA, typicalStudentStatus, employed full-time]
-
A.
academicStatus
Indicates the educational or scholarly standing or level an entity holds within an academic context.
-
B.
studentOrAssistant
Indicates that an individual has the role of either a student or an assistant in a given context or relationship.
-
C.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
-
D.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
-
E.
typicalStudentAssignment
Indicates that an assignment is a standard or commonly expected task given to a student in a particular educational context.
- 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_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. |
| PDg | Predicate description generation | batch_69abbfe93d7c81909f1b9c1b1e3c7989 |
completed | March 7, 2026, 6:04 a.m. |
Created at: March 4, 2026, 7:47 p.m.