Triple
T37836687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ლევან კობიაშვილი |
E943355
|
entity |
| Predicate | როლით_ცნობილია |
P140036
|
FINISHED |
| Object | ბუნდესლიგაში წარმატებული ქართველი ლეგიონერი |
—
|
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: ბუნდესლიგაში წარმატებული ქართველი ლეგიონერი | Statement: [ლევან კობიაშვილი, როლით_ცნობილია, ბუნდესლიგაში წარმატებული ქართველი ლეგიონერი]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: როლით_ცნობილია Context triple: [ლევან კობიაშვილი, როლით_ცნობილია, ბუნდესლიგაში წარმატებული ქართველი ლეგიონერი]
-
A.
knownForRoleIn
chosen
Indicates that an entity is recognized or notable for performing a particular role in a specific work, project, or context.
-
B.
famousRole
Indicates that an entity is best known for portraying or performing a particular role or character.
-
C.
როლები
Indicates that an entity has specific roles, functions, or positions assigned or associated with it in a given context.
-
D.
notableWorkRole
Indicates that a person’s role or position is specifically associated with the creation, performance, or contribution to a notable work.
-
E.
известенКак
Indicates that one entity is known or recognized by a particular name, title, or role.
- 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_69f76eeb0f7081908d6d3adbc469889c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbae559a8819086ef839973f8d9b2 |
completed | May 6, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69fbb1440fa08190abf25ba684f75b6e |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.