Triple
T5449740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Bergen |
E122338
|
entity |
| Predicate | hasStaffSize |
P23565
|
FINISHED |
| Object | over 4,000 employees |
—
|
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: over 4,000 employees | Statement: [University of Bergen, hasStaffSize, over 4,000 employees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStaffSize Context triple: [University of Bergen, hasStaffSize, over 4,000 employees]
-
A.
staffSize
chosen
Indicates the number of staff members associated with an entity.
-
B.
hasEmployees
Indicates that one entity employs one or more other entities as its workers or staff.
-
C.
hasGeneralStaff
Indicates that an entity has, is associated with, or is served by a general staff body responsible for overall strategic or administrative functions.
-
D.
staffingLevel
Indicates the degree or adequacy of personnel assigned to perform a particular function, task, or operation.
-
E.
hasAudienceSize
Indicates the relationship between an entity and the number of people or size of group that receives, views, or engages with it.
- 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_69bd4640f52c81909e653ec361f66d76 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd95be329c81908783420cf81b6af5 |
completed | March 20, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69bd919e8d18819098c4af6a015e5cc2 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:07 p.m.