Triple
T5149106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Agriculture, Kobe University |
E116146
|
entity |
| Predicate | hasAcademicStaffRole |
P298
|
FINISHED |
| Object | professor |
—
|
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: professor | Statement: [Faculty of Agriculture, Kobe University, hasAcademicStaffRole, professor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAcademicStaffRole Context triple: [Faculty of Agriculture, Kobe University, hasAcademicStaffRole, professor]
-
A.
hasAcademicStaff
Indicates that an institution or organization employs or is associated with one or more academic staff members.
-
B.
hasAcademicFunction
Indicates that an entity serves a specific academic role, duty, or function within an educational or scholarly context.
-
C.
hasAcademicOffice
Indicates that an entity maintains or occupies an official academic office or workspace associated with an educational or research institution.
-
D.
hasAcademicRank
chosen
Indicates that an entity holds a specific academic rank or title within an educational or research institution.
-
E.
hasTeachingRole
Indicates that one entity holds a position or responsibility involving teaching or instruction in relation to another entity.
- 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_69bd4446c0e08190a7c29dc74976bf03 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78d7f4d081908d59adcd86f52f1d |
completed | March 20, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69bd77ae2f10819098bb8939106e1281 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:43 p.m.