Triple
T26233725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victorian TAFE system |
E656109
|
entity |
| Predicate | hasEducationSector |
P89500
|
FINISHED |
| Object | tertiary education |
—
|
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: tertiary education | Statement: [Victorian TAFE system, hasEducationSector, tertiary education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationSector Context triple: [Victorian TAFE system, hasEducationSector, tertiary education]
-
A.
educationalSector
chosen
Indicates a relationship in which something is part of, associated with, or operates within the education or schooling domain.
-
B.
educatesForSector
Indicates that an entity provides education or training specifically aimed at preparing individuals for a particular sector or industry.
-
C.
operatesInEducationalSector
Indicates that an entity conducts its primary activities or provides services within the field of education or the educational industry.
-
D.
educationSectorStatus
Indicates the condition or state of the education sector in relation to a given context or time.
-
E.
hasEducationServices
Indicates that one entity provides or offers educational services to another entity or within a particular context.
- 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_69ee5b4b8b408190993da38c0067cc8d |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 26, 2026, 9 p.m.