Triple
T1326269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of California, Santa Barbara |
E28333
|
entity |
| Predicate | academicStaffCountApprox |
P26574
|
FINISHED |
| Object | 1000+ |
—
|
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: 1000+ | Statement: [University of California, Santa Barbara, academicStaffCountApprox, 1000+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicStaffCountApprox Context triple: [University of California, Santa Barbara, academicStaffCountApprox, 1000+]
-
A.
hasAcademicStaff
Indicates that an institution or organization employs or is associated with one or more academic staff members.
-
B.
numberOfFaculties
Indicates the total count of faculties associated with a given entity.
-
C.
publicUniversityFaculty
Indicates that a person is a member of the faculty (e.g., professor, lecturer, instructor) at a public university.
-
D.
hasDoctoralStudents
Indicates that a person serves as the doctoral advisor or supervisor of one or more doctoral students.
-
E.
academicType
Indicates the specific academic category or classification associated with an entity (such as a work, program, or role).
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69a4bf8158ac8190b8360ecccc2980bc |
completed | March 1, 2026, 10:36 p.m. |
Created at: March 1, 2026, 7:55 p.m.