Triple
T1326270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of California, Santa Barbara |
E28333
|
entity |
| Predicate | studentEnrollmentApprox |
P21454
|
FINISHED |
| Object | 25000+ |
—
|
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: 25000+ | Statement: [University of California, Santa Barbara, studentEnrollmentApprox, 25000+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studentEnrollmentApprox Context triple: [University of California, Santa Barbara, studentEnrollmentApprox, 25000+]
-
A.
studentPopulationLevel
chosen
Indicates the relative size or magnitude of the student population associated with an entity.
-
B.
undergraduateEnrollment
Indicates the number of undergraduate students enrolled in an institution or program.
-
C.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
-
D.
servesStudentPopulation
Indicates that an entity provides services, resources, or support to a defined group of students.
-
E.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19fd2648190932a85eacb3e7ec4 |
completed | March 1, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69a4beedb49c8190beb5b85cdda05013 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.