Triple
T1712826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UAH |
E37220
|
entity |
| Predicate | hasSubunitToUnitRatio |
P507
|
FINISHED |
| Object | 100 kopiykas = 1 hryvnia |
—
|
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: 100 kopiykas = 1 hryvnia | Statement: [UAH, hasSubunitToUnitRatio, 100 kopiykas = 1 hryvnia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubunitToUnitRatio Context triple: [UAH, hasSubunitToUnitRatio, 100 kopiykas = 1 hryvnia]
-
A.
subunitRatio
chosen
Indicates the proportional relationship between the quantities or sizes of different subunits within a larger whole.
-
B.
subunitOf
Indicates that one entity functions as a component or smaller part within the structure or organization of another, larger entity.
-
C.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
D.
isDivisibleUnitOf
Indicates that one unit can be evenly divided into another unit, such that the second unit is an exact multiple or fraction of the first.
-
E.
usesSameSubunitStructureAs
Indicates that two entities share an identical or equivalent arrangement and composition of their constituent subunits within a larger structural framework.
- 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab7521878c8190b9e7739b8c3fc705 |
completed | March 7, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69aa61bd46d48190915500d75a9d8e94 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.