Triple
T2238628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samy Bengio |
E49340
|
entity |
| Predicate | hasTaughtSubject |
P34091
|
FINISHED |
| Object | machine learning |
—
|
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: machine learning | Statement: [Samy Bengio, hasTaughtSubject, machine learning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTaughtSubject Context triple: [Samy Bengio, hasTaughtSubject, machine learning]
-
A.
hasTeaching
Indicates that one entity provides instruction or educational guidance to another entity.
-
B.
taughtCourse
chosen
Indicates that an entity (typically an instructor) has taught a particular course.
-
C.
hasTeachingActivity
Indicates that an entity engages in or is associated with a specific teaching-related activity or instructional role.
-
D.
isTaughtAs
Indicates that something is presented or delivered as instructional content, typically within an educational or training context.
-
E.
hasLecturer
Indicates that an educational course, class, or module is taught or overseen by a specific lecturer.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc096c7748190a545cc9b229bde62 |
completed | March 7, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69abbdafc07881909101266a33ae7031 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.