Triple
T5027325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Florida |
E113208
|
entity |
| Predicate | enrollment |
P60599
|
FINISHED |
| Object | over 50,000 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: over 50,000 students | Statement: [University of Florida, enrollment, over 50,000 students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enrollment Context triple: [University of Florida, enrollment, over 50,000 students]
-
A.
enrollmentModel
Indicates the type or structure of the enrollment relationship that governs how entities (such as users or participants) are registered or associated with a program, course, or service.
-
B.
enrollmentType
Indicates the specific category or mode under which an entity is enrolled in a program, service, or system.
-
C.
enrolledForm
Indicates that an entity is formally registered or signed up to participate in a particular form, program, or course.
-
D.
enrollmentLevel
Indicates the degree or status of participation an entity has in a particular enrollment context (such as a program, course, or service).
-
E.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
- 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_69bd443775e48190a646ffbfc4334723 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd738d852c8190a122354f1e1f5343 |
completed | March 20, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69bd71509e9c8190a60c1d8d04936a12 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd724ff2b4819091351cf80d3647a1 |
completed | March 20, 2026, 4:14 p.m. |
Created at: March 20, 2026, 1:36 p.m.