Triple
T2648056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Université de Versailles Saint-Quentin-en-Yvelines |
E53829
|
entity |
| Predicate | awardsDegree |
P49
|
FINISHED |
| Object | Licence |
—
|
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: Licence | Statement: [Université de Versailles Saint-Quentin-en-Yvelines, awardsDegree, Licence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardsDegree Context triple: [Université de Versailles Saint-Quentin-en-Yvelines, awardsDegree, Licence]
-
A.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
B.
hasDegree
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
-
C.
grantsDegreesFrom
Indicates that an institution has the authority to confer academic degrees originating from a specified source or program.
-
D.
graduatedWithHonors
Indicates that an entity completed an academic program with a distinction or honors-level achievement according to the institution’s criteria.
-
E.
offersDegree
chosen
Indicates that an institution or program provides a specific academic degree as an available qualification.
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd91b4b3c81908571e85a1621dfc5 |
completed | March 7, 2026, 7:51 a.m. |
| PD | Predicate disambiguation | batch_69abd814298c8190952f05aed43f6bb8 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.