Triple
T38157417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | მიხეილ სააკაშვილი |
E952922
|
entity |
| Predicate | იმყოფებოდა |
P190162
|
FINISHED |
| Object | საქართველოს ციხეში 2020-იან წლებში |
—
|
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: საქართველოს ციხეში 2020-იან წლებში | Statement: [მიხეილ სააკაშვილი, იმყოფებოდა, საქართველოს ციხეში 2020-იან წლებში]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: იმყოფებოდა Context triple: [მიხეილ სააკაშვილი, იმყოფებოდა, საქართველოს ციხეში 2020-იან წლებში]
-
A.
podlegała
Indicates that one entity was subordinate to, under the authority of, or subject to the control or jurisdiction of another entity in the past.
-
B.
dissolved
Indicates that one substance has been mixed into another so thoroughly that it forms a uniform solution and is no longer distinguishable as a separate phase.
-
C.
fell
Indicates that an entity moved downward from a higher position to a lower one, typically due to gravity, often unintentionally or uncontrollably.
-
D.
posedIn
Indicates that an entity assumed a particular physical position or posture, typically for the purpose of being observed, photographed, drawn, or otherwise depicted.
-
E.
impregnatedBy
Indicates that one entity has caused another entity to become pregnant.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69fcb088aac481909db90804faff315f |
completed | May 7, 2026, 3:32 p.m. |
Created at: May 3, 2026, 4:21 p.m.