Triple
T22407907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Nigeria Secondary School |
E553923
|
entity |
| Predicate | hasNotableFieldOfAlumni |
P92502
|
FINISHED |
| Object | literature |
—
|
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: literature | Statement: [University of Nigeria Secondary School, hasNotableFieldOfAlumni, literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableFieldOfAlumni Context triple: [University of Nigeria Secondary School, hasNotableFieldOfAlumni, literature]
-
A.
hasNotableFacultyAlumnus
Indicates that an individual is a distinguished former student who is recognized as notable faculty at a given institution.
-
B.
hasNotableAlumniType
Indicates that an entity has notable alumni belonging to a specified category or type.
-
C.
hasNotableAlumniInstitution
Indicates that an institution is associated with one or more notable alumni who previously attended or graduated from it.
-
D.
hasNotableFacultyField
Indicates that an institution’s notable faculty are associated with or specialize in a particular academic or professional field.
-
E.
hasAlumniField
chosen
Indicates a relationship where an entity is associated with a specific field or area of study in which its alumni specialized or graduated.
- 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_69e11e4e6ce8819085a1e06d886bf21c |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158ba1c6481908e4b9b3635ed3a49 |
completed | April 29, 2026, 1:02 a.m. |
| PD | Predicate disambiguation | batch_69e8989495bc81909d2699fce5992e28 |
completed | April 22, 2026, 9:44 a.m. |
Created at: April 16, 2026, 8:46 p.m.