Triple
T6573432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Health Sciences (University of Ottawa) |
E155498
|
entity |
| Predicate | usesBilingualInstruction |
P71934
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Faculty of Health Sciences (University of Ottawa), usesBilingualInstruction, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBilingualInstruction Context triple: [Faculty of Health Sciences (University of Ottawa), usesBilingualInstruction, true]
-
A.
isBilingual
Indicates that an entity is able to communicate fluently in two distinct languages.
-
B.
alsoUsesLanguageOfInstruction
Indicates that an entity, in addition to its primary language, uses the same language that is designated as the language of instruction in a given context.
-
C.
primaryLanguageOfInstruction
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
D.
isBilingualRegion
Indicates that a region officially uses two languages or has two predominant languages in regular use.
-
E.
hasSecondaryLanguage
Indicates that an entity possesses or uses a secondary language in addition to its primary language.
- 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_69c688151254819080387f87deab8fa7 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6acf93cb48190b54f5dd6febd34dc |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6cc988c0081909d22b86ca299331c |
completed | March 27, 2026, 6:29 p.m. |
Created at: March 27, 2026, 1:53 p.m.