Triple
T19101935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tbilisi Knowledge Hub |
E467552
|
entity |
| Predicate | typeOfCenter |
P11544
|
FINISHED |
| Object | regional hub |
—
|
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: regional hub | Statement: [Tbilisi Knowledge Hub, typeOfCenter, regional hub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCenter Context triple: [Tbilisi Knowledge Hub, typeOfCenter, regional hub]
-
A.
centerType
chosen
Indicates the classification or category of a center (e.g., type of facility, institution, or hub) associated with an entity.
-
B.
hasCenterType
Indicates that something is characterized by or assigned a specific type or category of center.
-
C.
formsCenterOf
Indicates that one entity constitutes the central or core part of another entity.
-
D.
politicalCenterType
Indicates the type or classification of a political center associated with an entity.
-
E.
typeOfGovernmentCenter
Indicates the specific form or classification of governmental authority that a particular administrative center serves or represents.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e36e9bfc8190bbaccab169394d99 |
completed | April 20, 2026, 8:27 a.m. |
| PD | Predicate disambiguation | batch_69e4b9ac41848190afd0f33b42cebe99 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:04 p.m.