Triple
T11487356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIU blue |
E272312
|
entity |
| Predicate | organizationTypeUser |
P3580
|
FINISHED |
| Object | public research university |
—
|
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: public research university | Statement: [FIU blue, organizationTypeUser, public research university]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: organizationTypeUser Context triple: [FIU blue, organizationTypeUser, public research university]
-
A.
organizationType
chosen
Indicates the specific category or classification of an organization in terms of its nature, structure, or primary function.
-
B.
governingBodyUser
Indicates that a user acts as a governing or decision-making authority for a particular entity or organization.
-
C.
organizationTypeLed
Indicates that an entity holds a leadership role over an organization of a specified type.
-
D.
partnerInOrganizationWith
Indicates that two entities are associated as partners within the same organization or organizational context.
-
E.
administrativeUnitType
Indicates the specific kind or category of administrative unit involved in the relationship (e.g., city, county, province).
- 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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85a1fc9688190aacc2eed64229b79 |
completed | April 10, 2026, 2:02 a.m. |
| PD | Predicate disambiguation | batch_69d808736c5c8190899b5b3b2e797f65 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:36 p.m.