Triple
T38324580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | აკაკი წერეთლის ძეგლი თბილისში |
E1036748
|
entity |
| Predicate | განთავსებულია |
P190644
|
FINISHED |
| Object | საქართველოს დედაქალაქი |
—
|
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 დედაქალაქი | Statement: [აკაკი წერეთლის ძეგლი თბილისში, განთავსებულია, საქართველოს დედაქალაქი]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: განთავსებულია Context triple: [აკაკი წერეთლის ძეგლი თბილისში, განთავსებულია, საქართველოს დედაქალაქი]
-
A.
containedWith
Indicates that one entity is located or kept inside the bounds or interior space of another entity.
-
B.
გაიმარჯვა
Indicates that one entity has won or achieved victory over others in a competition, contest, or conflict.
-
C.
agedIn
Indicates that one entity has been stored or matured within another entity (such as a container or location) for a period of time, typically to develop certain qualities.
-
D.
დააკავეს
Indicates that someone was arrested or taken into custody by an authority.
-
E.
განახორციელა
Indicates that an entity has carried out or implemented a specific action, task, or project.
- 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_69f76e1c16fc8190bde982289dd5106b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fccbd826708190b5fab12c4236299a |
completed | May 7, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69fcc58838e08190b8fa54aa5c165f2d |
completed | May 7, 2026, 5:02 p.m. |
| PDg | Predicate description generation | batch_69fccbd6b7688190b746803cf78d5704 |
completed | May 7, 2026, 5:28 p.m. |
Created at: May 3, 2026, 4:30 p.m.