Triple
T2411251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State University System of Florida |
E52193
|
entity |
| Predicate | hasNumberOfInstitutions |
P276
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [State University System of Florida, hasNumberOfInstitutions, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfInstitutions Context triple: [State University System of Florida, hasNumberOfInstitutions, 12]
-
A.
hasNumberOfMemberInstitutions
chosen
Indicates the quantitative count of member institutions associated with a given entity.
-
B.
numberOfTargetInstitutions
Indicates the count of institutions that are designated or identified as targets in a given context or dataset.
-
C.
establishedInstitution
Indicates that an entity founded, created, or formally set up an institution or organization.
-
D.
hasStateInstitution
Indicates that a particular state possesses, governs, or is served by a specific institution operating under its authority or within its jurisdiction.
-
E.
associatedWithInstitution
Indicates that an entity has a formal or recognized connection or affiliation with an institution.
- 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_69ab495622948190bc6bc6e4cddaf645 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc928fd608190885fcde6746a06bc |
completed | March 7, 2026, 6:43 a.m. |
| PD | Predicate disambiguation | batch_69abc5a6cbd0819086c0716e266b7ebb |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 6, 2026, 9:41 p.m.