Triple
T19410601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New South Wales Higher School Certificate |
E485575
|
entity |
| Predicate | hasSubjectTypes |
P135767
|
FINISHED |
| Object | Board Developed Courses |
—
|
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: Board Developed Courses | Statement: [New South Wales Higher School Certificate, hasSubjectTypes, Board Developed Courses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectTypes Context triple: [New South Wales Higher School Certificate, hasSubjectTypes, Board Developed Courses]
-
A.
hasObjectiveTypes
Indicates that an entity is associated with one or more specific types or categories of objectives it aims to achieve.
-
B.
hasSubjectCount
Indicates that an entity is associated with a specific number of subjects.
-
C.
hasSubjectEntries
Indicates that an entity is associated with one or more subject-related records or entries.
-
D.
hasCollectionSubject
Indicates that a collection is about or thematically centered on a particular subject.
-
E.
hasSubjectEntriesIn
Indicates that a subject is recorded or represented within specific entries of a collection, dataset, or catalog.
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62af4cc0c81909056b5e2ee574ab1 |
completed | April 20, 2026, 1:32 p.m. |
| PD | Predicate disambiguation | batch_69e4fd68b1f881908d273de1fee81a75 |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004c23308190a087b7941a90725f |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:37 p.m.