Triple
T8553126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Marketing |
E202492
|
entity |
| Predicate | institutionalRole |
P13957
|
FINISHED |
| Object | teaching |
—
|
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: teaching | Statement: [Faculty of Marketing, institutionalRole, teaching]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: institutionalRole Context triple: [Faculty of Marketing, institutionalRole, teaching]
-
A.
roleAtInstitution
Indicates that an entity holds or has held a specific role or position within a particular institution.
-
B.
campusRole
Indicates the specific position, function, or capacity an individual holds within a campus or academic institution.
-
C.
hasOrganizationalRole
chosen
Indicates that an entity holds a specific role, position, or function within an organization.
-
D.
inInstitution
Indicates that an entity is located within, belongs to, or is formally associated with a particular institution.
-
E.
hasAcademicPrecinctRole
Indicates that an entity holds a specific role or position within an academic precinct or campus area.
- 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_69ca832610e08190b3b6c6cd2c250255 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe8882704819094b688d46169433a |
completed | March 31, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69cbd113e05c81908f4f3fc1b5925164 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:19 p.m.