Triple
T16173653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UPVM3 |
E392504
|
entity |
| Predicate | hasInstitutionalSector |
P121996
|
FINISHED |
| Object | tertiary education |
—
|
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: tertiary education | Statement: [UPVM3, hasInstitutionalSector, tertiary education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInstitutionalSector Context triple: [UPVM3, hasInstitutionalSector, tertiary education]
-
A.
hasInstitutions
Indicates that one entity possesses, contains, or is associated with one or more institutions.
-
B.
hasInstitutionalCharacter
Indicates that something possesses qualities, status, or attributes associated with a formal institution or institutional framework.
-
C.
hasInstitutionalHome
Indicates that an entity is formally based in, hosted by, or affiliated with a particular institution as its organizational home.
-
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.
hasInstitutionalPresenceIn
Indicates that an institution maintains an established presence, such as operations, offices, or activities, within a specified location or region.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21eb9b8208190b60874cec7a3a98e |
completed | April 17, 2026, 11:51 a.m. |
| PD | Predicate disambiguation | batch_69e219d642708190ba31a90dce76a210 |
completed | April 17, 2026, 11:30 a.m. |
| PDg | Predicate description generation | batch_69e21e55a2388190b29a045a8c608ba4 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:02 a.m.