Triple
T10116418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schulich Leader Scholarships |
E218370
|
entity |
| Predicate | maximumScienceScholarshipValueCAD |
P37671
|
FINISHED |
| Object | 80000 |
—
|
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: 80000 | Statement: [Schulich Leader Scholarships, maximumScienceScholarshipValueCAD, 80000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumScienceScholarshipValueCAD Context triple: [Schulich Leader Scholarships, maximumScienceScholarshipValueCAD, 80000]
-
A.
scholarshipType
Indicates the specific category or kind of scholarship associated with an entity.
-
B.
maximumGrantAmount
chosen
Indicates the highest monetary value that can be awarded or granted under a specific grant, program, or agreement.
-
C.
scholarshipEquivalency
Indicates that one scholarship is considered equal in value, coverage, or benefit to another scholarship or financial award.
-
D.
maximumScholarshipsPerTeam
Indicates the highest number of scholarships that any single team is allowed to award or hold.
-
E.
hasOrganScholarships
Indicates that an entity offers or provides scholarships specifically related to organ study or performance.
- 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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd162fac0819084c74947c1f6688e |
completed | April 2, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9ed7e48190aa132ef8a69b49f9 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:04 p.m.