Triple
T6414093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Campus Saint-Jean |
E127779
|
entity |
| Predicate | academicEnvironment |
P19810
|
FINISHED |
| Object | bilingual |
—
|
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: bilingual | Statement: [Campus Saint-Jean, academicEnvironment, bilingual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicEnvironment Context triple: [Campus Saint-Jean, academicEnvironment, bilingual]
-
A.
academicContext
chosen
Indicates the educational or scholarly setting, framework, or circumstances within which an activity, relationship, or piece of information takes place.
-
B.
academicType
Indicates the specific academic category or classification associated with an entity (such as a work, program, or role).
-
C.
academicUse
Indicates that something is intended for, suitable for, or used within an academic or educational context.
-
D.
academicStructure
Indicates a hierarchical or organizational relationship within an academic system, such as how programs, departments, courses, or degrees are structured and related to one another.
-
E.
academicAdvisor
Indicates that one entity serves as the academic advisor, providing formal guidance and oversight on academic matters, to another 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_69c0083815208190a9b299b8e0640218 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c068e5187c8190a6be1b934e0f1b3a |
completed | March 22, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69c060f5d4e481909d1366190607b586 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:42 p.m.