Triple
T23539905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collège Montmorency |
E577712
|
entity |
| Predicate | servesStudentPopulationFrom |
P88189
|
FINISHED |
| Object | Greater Montreal area |
—
|
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: Greater Montreal area | Statement: [Collège Montmorency, servesStudentPopulationFrom, Greater Montreal area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesStudentPopulationFrom Context triple: [Collège Montmorency, servesStudentPopulationFrom, Greater Montreal area]
-
A.
servesStudentPopulation
Indicates that an entity provides services, resources, or support to a defined group of students.
-
B.
studentPopulationLevel
Indicates the relative size or magnitude of the student population associated with an entity.
-
C.
primaryStudentPopulation
Indicates the number or group of students who are enrolled at the primary or elementary level within an educational institution or system.
-
D.
admitsStudentsFrom
chosen
Indicates that an educational institution accepts or enrolls students who come from a specified source, such as a school, region, or program.
-
E.
hasNumberOfSchools
Indicates the quantity of schools associated with a given entity.
- 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_69e245f9d5d08190a4a20004e1784e20 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ae1a66b88190811b38523ea606fe |
completed | April 29, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69f118afabd88190bd88f49597d120e8 |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:10 p.m.