Triple
T15795664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ვახტანგ ჭაბუკიანი |
E382970
|
entity |
| Predicate | გავლენა |
P9
|
FINISHED |
| Object | ქართველი ბალეტის არტისტების მომდევნო თაობებზე |
—
|
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: ქართველი ბალეტის არტისტების მომდევნო თაობებზე | Statement: [ვახტანგ ჭაბუკიანი, გავლენა, ქართველი ბალეტის არტისტების მომდევნო თაობებზე]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: გავლენა Context triple: [ვახტანგ ჭაბუკიანი, გავლენა, ქართველი ბალეტის არტისტების მომდევნო თაობებზე]
-
A.
التأثير
Indicates a relationship where one entity produces a change or has an influence on another entity or its state.
-
B.
influenced
chosen
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
C.
encodingImpact
Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or outcome.
-
D.
hasSignificantInfluenceIn
Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
-
E.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4dc887081909d682ae153f06d97 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:48 a.m.