Triple
T37836668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ლევან კობიაშვილი |
E943355
|
entity |
| Predicate | საკლუბო_კარიერა_ქვეყანა |
P79304
|
FINISHED |
| Object | საქართველო |
—
|
NE NERFINISHED |
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: საქართველო | Statement: [ლევან კობიაშვილი, საკლუბო_კარიერა_ქვეყანა, საქართველო]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: საკლუბო_კარიერა_ქვეყანა Context triple: [ლევან კობიაშვილი, საკლუბო_კარიერა_ქვეყანა, საქართველო]
-
A.
countryOfClubCareer
chosen
Indicates the country in which an entity’s club-level sports career took place or is associated.
-
B.
countryOfClubPlayedFor
Indicates the country in which the club that an entity played for is based.
-
C.
sportsCareer
Indicates a relationship where an entity’s professional involvement, roles, or achievements in sports are associated with a particular sport, team, period, or competitive level.
-
D.
clubCareerEnd
Indicates the point in time or event at which an entity’s involvement in a club-level career comes to an end.
-
E.
clubOrNational
Indicates that the relationship or action involves either a club team or a national team, distinguishing between those two types of affiliations.
- 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_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd166a488190b1bf9316b0790801 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:19 p.m.