Triple
T8622169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kutaisi urban area |
E204191
|
entity |
| Predicate | containsInstitutionType |
P3814
|
FINISHED |
| Object | universities |
—
|
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: universities | Statement: [Kutaisi urban area, containsInstitutionType, universities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsInstitutionType Context triple: [Kutaisi urban area, containsInstitutionType, universities]
-
A.
supportsInstitutionType
Indicates that one entity provides backing, resources, or endorsement specifically for a particular type or category of institution.
-
B.
typeOfInstitution
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
C.
includesInstitution
chosen
Indicates that one entity contains, encompasses, or has as a member a particular institution.
-
D.
hasPrimaryInstitutionType
Indicates that an entity’s main or principal institutional classification or category is of a specified type.
-
E.
associatedInstitutionType
Indicates the type or category of institution with which an entity is associated.
- 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_69ca834a4ea0819094970dceb9e389f3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:26 p.m.