Triple
T231009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Geneva |
E4409
|
entity |
| Predicate | hasStudentBodyCharacteristic |
P5246
|
FINISHED |
| Object | international student population |
—
|
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: international student population | Statement: [University of Geneva, hasStudentBodyCharacteristic, international student population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentBodyCharacteristic Context triple: [University of Geneva, hasStudentBodyCharacteristic, international student population]
-
A.
hasStudentBodyType
chosen
Indicates that an educational institution possesses a student body characterized by a particular type or classification.
-
B.
studentBodySize
Indicates the total number of students that make up the student body of an institution or group.
-
C.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
D.
hasStudentOrganization
Indicates that an entity (such as an institution or department) is associated with or hosts a particular student organization.
-
E.
studentBodyFocus
Indicates that the primary attention, concern, or efforts are directed toward the student body as a whole.
- 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25e0868708190ad551ca06cc57f4a |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b5a075081909b0e9b88c1492d5a |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.