Triple
T25908539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unizar |
E652823
|
entity |
| Predicate | hasApproximateStudentBodyCategory |
P30984
|
FINISHED |
| Object | tens of thousands of students |
—
|
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: tens of thousands of students | Statement: [Unizar, hasApproximateStudentBodyCategory, tens of thousands of students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateStudentBodyCategory Context triple: [Unizar, hasApproximateStudentBodyCategory, tens of thousands of students]
-
A.
hasStudentBodyType
Indicates that an educational institution possesses a student body characterized by a particular type or classification.
-
B.
hasStudentBodyFrom
Indicates that an educational institution draws or enrolls its student body from a specified geographic area, group, or source.
-
C.
hasStudentCategory
Indicates that an entity is classified under a specific category or type of student.
-
D.
hasApproximateStudents
chosen
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
E.
studentBodySize
Indicates the total number of students that make up the student body of an institution or group.
- 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_69e7ab3d3f8481909bc53ed64c06af33 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6640168948190811bd5f933a87cf5 |
completed | May 2, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 22, 2026, 8:28 a.m.