Triple
T24394300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collège Stanislas de Montréal |
E614984
|
entity |
| Predicate | curriculumOrigin |
P156037
|
FINISHED |
| Object | France |
—
|
NE NERFINISHED |
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: France | Statement: [Collège Stanislas de Montréal, curriculumOrigin, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: curriculumOrigin Context triple: [Collège Stanislas de Montréal, curriculumOrigin, France]
-
A.
courseOrigin
Indicates that one entity is the source, starting point, or place of origin from which a course (such as a path, route, or curriculum) begins or is derived.
-
B.
curriculumType
Indicates the classification or category of curriculum associated with an educational program or course.
-
C.
usesCurriculum
Indicates that one entity adopts or applies a particular curriculum as the basis for its instruction, training, or educational activities.
-
D.
originatedInSchool
Indicates that an entity began, was first formed, or was initially developed within a particular school or educational institution.
-
E.
studentOrigin
Indicates that a student originates from, or is associated with, a particular place, institution, or source.
- F. None of above. chosen
Provenance (4 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_69e2d7e509b88190a53155d4f3de45ce |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2945afa80819094f7154f7539d0d1 |
completed | April 29, 2026, 11:29 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:04 a.m.