Triple
T18575453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nsukka |
E453973
|
entity |
| Predicate | hasHigherInstitutionType |
P124790
|
FINISHED |
| Object | federal university campus |
—
|
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: federal university campus | Statement: [Nsukka, hasHigherInstitutionType, federal university campus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHigherInstitutionType Context triple: [Nsukka, hasHigherInstitutionType, federal university campus]
-
A.
hasHigherEducationType
chosen
Indicates that one entity has a specified type or category of higher education associated with it.
-
B.
hasHigherEducationAccess
Indicates that one entity has access to higher education opportunities or institutions relative to another entity or context.
-
C.
hasHigherEducationHistory
Indicates that an entity has a record of having pursued or completed higher education studies in the past.
-
D.
hasCollegeType
Indicates that a college or educational institution is classified as having a specific type or category (e.g., public, private, community, technical).
-
E.
hasHighestDegree
Indicates that one entity possesses the highest academic degree attained by another entity.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543c9d26c8190a80dda411cd0c9ac |
completed | April 19, 2026, 9:06 p.m. |
| PD | Predicate disambiguation | batch_69e478c98d4c81909d37a0e72c6e7bd0 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:43 a.m.