Triple
T7742716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Patrick’s College, Ballina |
E175548
|
entity |
| Predicate | hasApproximateStudentAgeRange |
P73688
|
FINISHED |
| Object | 12–18 years |
—
|
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: 12–18 years | Statement: [St Patrick’s College, Ballina, hasApproximateStudentAgeRange, 12–18 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateStudentAgeRange Context triple: [St Patrick’s College, Ballina, hasApproximateStudentAgeRange, 12–18 years]
-
A.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
B.
hasDegreeRange
Indicates that an entity is associated with a minimum and maximum degree value defining a range.
-
C.
hasEnrollmentRange
Indicates that there is a specified minimum and/or maximum number of participants allowed or expected for an enrollment in a given context.
-
D.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
E.
supportsAgeRange
chosen
Indicates that one entity is compatible with, valid for, or designed to accommodate a specified range of ages.
- 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_69c6995f9c60819092e386192bd63c6f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70402169481909b219dc5f4a64b9b |
completed | March 27, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69c7016c4a748190a7012030edaefcee |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:07 p.m.