Triple
T24002339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Ottawa Faculty of Medicine |
E594279
|
entity |
| Predicate | teachesProfession |
P25982
|
FINISHED |
| Object | physician |
—
|
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: physician | Statement: [University of Ottawa Faculty of Medicine, teachesProfession, physician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachesProfession Context triple: [University of Ottawa Faculty of Medicine, teachesProfession, physician]
-
A.
taughtAs
Indicates that one entity served as a teacher or instructor for another entity in an educational or training context.
-
B.
definedTeaching
Indicates that one entity has formally specified or established the teaching content, method, or curriculum for another entity.
-
C.
hasTeaching
chosen
Indicates that one entity provides instruction or educational guidance to another entity.
-
D.
hasTeachingRole
Indicates that one entity holds a position or responsibility involving teaching or instruction in relation to another entity.
-
E.
teacherInText
Indicates that an entity functions as a teacher within the context or narrative of a given text.
- 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_69e288b9ecf08190b8c94a278f5674fe |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d4663ca081908317db5c7ce99934 |
completed | April 29, 2026, 9:50 a.m. |
| PD | Predicate disambiguation | batch_69f17639d23c8190bed93434e2f9230a |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:39 p.m.