Triple
T24348854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigerian Air Force Military School, Jos |
E613725
|
entity |
| Predicate | hasCoreSubjects |
P36625
|
FINISHED |
| Object | mathematics |
—
|
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: mathematics | Statement: [Nigerian Air Force Military School, Jos, hasCoreSubjects, mathematics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoreSubjects Context triple: [Nigerian Air Force Military School, Jos, hasCoreSubjects, mathematics]
-
A.
hasSubjectOfStudy
chosen
Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
-
B.
hasPrimarySubject
Indicates that an entity is the main or principal subject associated with another entity or resource.
-
C.
hasPrimaryCourse
Indicates that an entity is associated with its main or principal course in a given context (such as a meal, curriculum, or sequence of offerings).
-
D.
hasCoreDegrees
Indicates that an entity possesses one or more primary or foundational academic degrees.
-
E.
hasCurriculumBasis
Indicates that one entity’s curriculum is founded on, derived from, or guided by another entity as its basis.
- 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_69e2d7ddd29481909e7f539a6072bd71 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293430524819087984a699d1d3687 |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287bb1b2c81909c2e7fcc392ad143 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:58 a.m.