Triple
T3921068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macedonian denar |
E88958
|
entity |
| Predicate | fractionalUnitRatio |
P32237
|
FINISHED |
| Object | 1 denar = 100 deni |
—
|
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 denar = 100 deni | Statement: [Macedonian denar, fractionalUnitRatio, 1 denar = 100 deni]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fractionalUnitRatio Context triple: [Macedonian denar, fractionalUnitRatio, 1 denar = 100 deni]
-
A.
fractionalUnitSymbol
Indicates the symbolic notation used to represent the fractional unit associated with a given quantity or measurement.
-
B.
fractionalUnitNameInFrench
Indicates the French-language name used for a fractional unit associated with another quantity or measure.
-
C.
minorUnitsPerUnit
chosen
Indicates the number of smaller sub-units that collectively make up one whole unit in a given measurement or currency system.
-
D.
subunitRatio
Indicates the proportional relationship between the quantities or sizes of different subunits within a larger whole.
-
E.
hasFraction
Indicates that one entity represents a fractional part or proportion of another entity.
- 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_69aed955229881909e85e73ffab1d343 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee75eedcc81908088ff4dbb8be56b |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.