Triple
T38157384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | მიხეილ სააკაშვილი |
E952922
|
entity |
| Predicate | განათლება მიიღო |
P5
|
FINISHED |
| Object | კიევის სახელმწიფო უნივერსიტეტი |
—
|
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: კიევის სახელმწიფო უნივერსიტეტი | Statement: [მიხეილ სააკაშვილი, განათლება მიიღო, კიევის სახელმწიფო უნივერსიტეტი]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: განათლება მიიღო Context triple: [მიხეილ სააკაშვილი, განათლება მიიღო, კიევის სახელმწიფო უნივერსიტეტი]
-
A.
receivedEducationGrant
Indicates that an entity has been awarded or obtained an education-related grant from another entity or funding source.
-
B.
hasEducationalAchievement
Indicates that an entity has attained a specific level, degree, or form of formal educational accomplishment.
-
C.
learnedIn
Indicates that an entity acquired knowledge, skills, or information within a particular context, environment, or source.
-
D.
educatedAt
chosen
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
E.
receivedTrainingIn
Indicates that one entity has undergone or been provided with training or instruction in a particular field, skill, or subject associated with another entity.
- 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.