Triple
T16345843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Veterinary Medicine, Bayero University Kano |
E396927
|
entity |
| Predicate | professionalOutcome |
P123056
|
FINISHED |
| Object | qualification to practice as veterinarian 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: qualification to practice as veterinarian in Nigeria | Statement: [Faculty of Veterinary Medicine, Bayero University Kano, professionalOutcome, qualification to practice as veterinarian in Nigeria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalOutcome Context triple: [Faculty of Veterinary Medicine, Bayero University Kano, professionalOutcome, qualification to practice as veterinarian in Nigeria]
-
A.
professionalWins
Indicates that one entity has achieved a certain number of victories or successes in a professional context, such as in a career, competition, or formal domain.
-
B.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
C.
professionalCompetence
Indicates that one entity possesses the necessary skills, knowledge, and ability to perform a professional role or task to an acceptable standard in relation to another entity or context.
-
D.
professional
Indicates that one entity has a formal, occupation-related role, service, or expertise in relation to another entity.
-
E.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
- 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2da0ec7e08190982a0de8ba5da105 |
completed | April 18, 2026, 1:10 a.m. |
| PD | Predicate disambiguation | batch_69e226eba9b48190af6e80d3d1c2aed3 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:07 a.m.