Triple
T1838173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ethiopian birr |
E41112
|
entity |
| Predicate | hasSubunitRatio |
P32237
|
FINISHED |
| Object | 1 birr = 100 santim |
—
|
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: 1 birr = 100 santim | Statement: [Ethiopian birr, hasSubunitRatio, 1 birr = 100 santim]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubunitRatio Context triple: [Ethiopian birr, hasSubunitRatio, 1 birr = 100 santim]
-
A.
subunitRatio
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.
usesSameSubunitStructureAs
Indicates that two entities share an identical or equivalent arrangement and composition of their constituent subunits within a larger structural framework.
-
D.
minorUnitsPerUnit
chosen
Indicates the number of smaller sub-units that collectively make up one whole unit in a given measurement or currency system.
-
E.
minorUnitSubdivisions
Indicates that one administrative or organizational unit is subdivided into smaller, subordinate units.
- 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafd88ebc81908208394746351fe6 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:33 p.m.