Triple
T15259762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coolum State High School |
E364742
|
entity |
| Predicate | hasStudentGenderAdmission |
P16158
|
FINISHED |
| Object | mixed |
—
|
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: mixed | Statement: [Coolum State High School, hasStudentGenderAdmission, mixed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentGenderAdmission Context triple: [Coolum State High School, hasStudentGenderAdmission, mixed]
-
A.
admissionGender
chosen
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
B.
formerGenderAdmission
Indicates that an institution previously admitted a particular gender but no longer does so.
-
C.
hasPupilsGender
Indicates that an entity has pupils whose gender is specified or characterized in some way.
-
D.
hasGenderRequirement
Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
-
E.
hasCoeducation
Indicates that an educational institution includes both male and female students together in its instructional programs.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0084d11148190919eef8e55569bb9 |
completed | April 15, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69deca8d1bd48190a4b94f29b425e335 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:13 a.m.