Triple
T14272434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Sturt University Orange campus |
E353822
|
entity |
| Predicate | primaryFocusArea |
P96519
|
FINISHED |
| Object | health 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: health education | Statement: [Charles Sturt University Orange campus, primaryFocusArea, health education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryFocusArea Context triple: [Charles Sturt University Orange campus, primaryFocusArea, health education]
-
A.
primaryArea
Indicates that one entity is the main or most important area, domain, or field associated with another entity.
-
B.
primarySubjectArea
chosen
Indicates the main academic or topical field to which something (such as a work, course, or resource) is most centrally related.
-
C.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
D.
primaryEngagement
Indicates the main or most significant interaction, involvement, or relationship that an entity has with another entity or activity.
-
E.
primaryInterest
Indicates that one entity is the main or most significant focus of attention, concern, or engagement for 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de65811d7c8190b075909a6570d415 |
completed | April 14, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a7d586c8190846ff242bbf5ac53 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.