Triple
T1819037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States International University Africa |
E40499
|
entity |
| Predicate | degreeSystem |
P32640
|
FINISHED |
| Object | credit-based 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: credit-based system | Statement: [United States International University Africa, degreeSystem, credit-based system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: degreeSystem Context triple: [United States International University Africa, degreeSystem, credit-based system]
-
A.
degreeAbbreviation
Indicates that one term is the abbreviated form of an academic degree represented by the other term.
-
B.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
C.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
-
D.
grantsDegreesFrom
Indicates that an institution has the authority to confer academic degrees originating from a specified source or program.
-
E.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
- 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba67721788190951beae25e885457 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61d884548190a19cf3a6b5ae9d48 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aba67554788190b429f2b9f0a70310 |
completed | March 7, 2026, 4:15 a.m. |
Created at: March 4, 2026, 7:32 p.m.