Triple
T13352686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Pharmacy, Ankara University |
E318106
|
entity |
| Predicate | academicStaffRole |
P29581
|
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 Pharmacy, Ankara University, academicStaffRole, teaching]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicStaffRole Context triple: [Faculty of Pharmacy, Ankara University, academicStaffRole, teaching]
-
A.
academicHead
Indicates that one entity serves as the chief academic leader or head of another entity, such as a department, program, or institution.
-
B.
academicChair
Indicates that one entity serves as the academic chair (leader or head) of a department, program, or academic unit associated with the other entity.
-
C.
hasAcademicStaff
Indicates that an institution or organization employs or is associated with one or more academic staff members.
-
D.
academicType
Indicates the specific academic category or classification associated with an entity (such as a work, program, or role).
-
E.
campusRole
chosen
Indicates the specific position, function, or capacity an individual holds within a campus or academic institution.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8d520881908aa23c7102b72b72 |
completed | April 11, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69d98f6fd8bc819086dddb6f376efa57 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:32 p.m.