Triple
T38157418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | მიხეილ სააკაშვილი |
E952922
|
entity |
| Predicate | გაიტანა პოლიტიკური საქმიანობა |
P150336
|
FINISHED |
| Object | საქართველოში |
—
|
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: საქართველოში | Statement: [მიხეილ სააკაშვილი, გაიტანა პოლიტიკური საქმიანობა, საქართველოში]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: გაიტანა პოლიტიკური საქმიანობა Context triple: [მიხეილ სააკაშვილი, გაიტანა პოლიტიკური საქმიანობა, საქართველოში]
-
A.
hasPoliticalActivityIn
chosen
Indicates that an entity engages in or is associated with political activities within a specified location or jurisdiction.
-
B.
politicalFunction
Indicates that an entity holds, performs, or is associated with a specific role, duty, or function within a political system or structure.
-
C.
politicallyIn
Indicates that one entity is located within, belongs to, or falls under the political jurisdiction or authority of another entity.
-
D.
enteredPoliticsIn
Indicates the point in time when an individual first began a career or active involvement in politics.
-
E.
professionBeforePolitics
Indicates that a person’s occupation or career occurred prior to their involvement in politics.
- 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_69f76f0b93c48190a117319ab3a9f282 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcb089a8f881909aa9e722babd43f7 |
completed | May 7, 2026, 3:32 p.m. |
| PD | Predicate disambiguation | batch_69fc45666c5c8190913bd632ac0e5b84 |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 3, 2026, 4:21 p.m.