Triple
T22395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of California |
E444
|
entity |
| Predicate | academicStaffSize |
P47
|
FINISHED |
| Object | one of the largest in the United States |
—
|
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: one of the largest in the United States | Statement: [University of California, academicStaffSize, one of the largest in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicStaffSize Context triple: [University of California, academicStaffSize, one of the largest in the United States]
-
A.
hasAcademicStaff
chosen
Indicates that an institution or organization employs or is associated with one or more academic staff members.
-
B.
academicStructure
Indicates a hierarchical or organizational relationship within an academic system, such as how programs, departments, courses, or degrees are structured and related to one another.
-
C.
hasFaculty
Indicates that an institution or department possesses or is associated with one or more faculty members.
-
D.
campusSize
Indicates the physical extent or scale of a campus, typically measured in area or capacity.
-
E.
hasAcademicAffiliation
Indicates that an entity is formally associated with an academic institution, such as through employment, enrollment, or official collaboration.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a24654724481909ba14b7f68d2a472 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.