Triple
T22418629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Pharmacy, Obafemi Awolowo University |
E554186
|
entity |
| Predicate | educatesForSector |
P148092
|
FINISHED |
| Object | healthcare sector in Nigeria |
—
|
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: healthcare sector in Nigeria | Statement: [Faculty of Pharmacy, Obafemi Awolowo University, educatesForSector, healthcare sector in Nigeria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educatesForSector Context triple: [Faculty of Pharmacy, Obafemi Awolowo University, educatesForSector, healthcare sector in Nigeria]
-
A.
educationalSector
Indicates a relationship in which something is part of, associated with, or operates within the education or schooling domain.
-
B.
educationalField
Indicates the academic or disciplinary area in which an educational activity, program, or qualification is focused.
-
C.
educationField
Indicates the academic or professional discipline in which an entity has been educated or trained.
-
D.
educationProvision
Indicates the act or arrangement of supplying educational services, resources, or opportunities to individuals or groups.
-
E.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
- 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_69e11e4e6ce8819085a1e06d886bf21c |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15948dcdc81909d0a792c4498fa70 |
completed | April 29, 2026, 1:05 a.m. |
| PD | Predicate disambiguation | batch_69e8989495bc81909d2699fce5992e28 |
completed | April 22, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69e8aa39e3388190b659d59948ebf3e6 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:46 p.m.