Triple
T17674279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bologna Process |
E440603
|
entity |
| Predicate | drivingPrinciple |
P128503
|
FINISHED |
| Object | voluntary intergovernmental cooperation |
—
|
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: voluntary intergovernmental cooperation | Statement: [Bologna Process, drivingPrinciple, voluntary intergovernmental cooperation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drivingPrinciple Context triple: [Bologna Process, drivingPrinciple, voluntary intergovernmental cooperation]
-
A.
drivesOn
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
B.
hasPrimaryDriver
Indicates that an entity is designated as the main or principal driver responsible for operating another entity, typically a vehicle.
-
C.
drives
Indicates that one entity operates and controls the movement of a vehicle or similar conveyance transporting themselves or others.
-
D.
drivingExperience
Indicates the extent or history of a person's involvement in driving vehicles, typically measured by duration, frequency, or level of skill.
-
E.
drivingSide
Indicates which side of the road (left or right) vehicles are required to drive on in a given jurisdiction.
- F. None of above. chosen
Provenance (4 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f6ba22081909e2099490c047378 |
completed | April 19, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69e3cde007d8819090dd92eea9f022cc |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 10 a.m.