Triple
T9993604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ontario Secondary School Diploma |
E196946
|
entity |
| Predicate | compulsoryCreditSubject |
P90343
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Ontario Secondary School Diploma, compulsoryCreditSubject, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compulsoryCreditSubject Context triple: [Ontario Secondary School Diploma, compulsoryCreditSubject, English]
-
A.
compulsoryEducation
Indicates that an entity is legally required to participate in a specified level or period of formal education.
-
B.
completionAsAcademicRequirementFor
chosen
Indicates that completing one entity is required to fulfill an academic requirement associated with another entity.
-
C.
requiresEducationIn
Indicates that one entity necessitates that another entity possess education or formal training in a specified field or discipline.
-
D.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
-
E.
usesAcademicCreditSystem
Indicates that an institution or program organizes and evaluates coursework using a formal academic credit system (e.g., credit hours or units).
- 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_69ca82f1678c819093d06320a05f16a4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcb982d5c81909779c6e9d780b399 |
completed | April 2, 2026, 1:51 a.m. |
| PD | Predicate disambiguation | batch_69cd1da07db88190945bcdab3ca82e71 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:50 p.m.