Triple
T3011720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | მტკვარი |
E82235
|
entity |
| Predicate | დაბინძურების_პრობლემა |
P18260
|
FINISHED |
| Object | ინდუსტრიული და საყოფაცხოვრებო ნარჩენებით დაბინძურების რისკი |
—
|
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: ინდუსტრიული და საყოფაცხოვრებო ნარჩენებით დაბინძურების რისკი | Statement: [მტკვარი, დაბინძურების_პრობლემა, ინდუსტრიული და საყოფაცხოვრებო ნარჩენებით დაბინძურების რისკი]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: დაბინძურების_პრობლემა Context triple: [მტკვარი, დაბინძურების_პრობლემა, ინდუსტრიული და საყოფაცხოვრებო ნარჩენებით დაბინძურების რისკი]
-
A.
problems
chosen
Indicates that one entity has issues, difficulties, or complications associated with or caused by another entity.
-
B.
conditions
Indicates that one entity specifies or imposes requirements, constraints, or circumstances that must be satisfied or hold true for another entity or situation.
-
C.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
D.
underlyingIssue
Indicates that one situation, problem, or condition is the fundamental cause or root problem behind another.
-
E.
diagnosedWith
Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a66c334819082d1d320c48eca1b |
completed | March 8, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69ad961a97188190809dc73430a8eda8 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3 p.m.