Triple
T12095256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Quentin-en-Yvelines campus |
E288054
|
entity |
| Predicate | hasStudentLifeFacility |
P2465
|
FINISHED |
| Object | student associations |
—
|
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: student associations | Statement: [Saint-Quentin-en-Yvelines campus, hasStudentLifeFacility, student associations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentLifeFacility Context triple: [Saint-Quentin-en-Yvelines campus, hasStudentLifeFacility, student associations]
-
A.
campusFacility
Indicates that one entity is a facility that is located on or belongs to a particular campus.
-
B.
hasCampusFeature
chosen
Indicates that a campus possesses or includes a specific physical or functional feature.
-
C.
campusFacilityType
Indicates the specific kind of facility a campus location is classified as (e.g., library, laboratory, residence hall).
-
D.
hasAcademicFacilities
Indicates that an entity provides or is equipped with academic facilities such as classrooms, laboratories, libraries, or other educational infrastructure.
-
E.
hasLectureHall
Indicates that an entity possesses, includes, or is associated with a lecture hall as part of its facilities or structure.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9178ad99c8190a54777b9bbe998bc |
completed | April 10, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69d915000454819089fee00022055599 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:48 p.m.