Triple
T2744072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bulgarian lev |
E60822
|
entity |
| Predicate | fractionalUnitNameSingular |
P6798
|
FINISHED |
| Object | stotinka |
—
|
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: stotinka | Statement: [Bulgarian lev, fractionalUnitNameSingular, stotinka]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fractionalUnitNameSingular Context triple: [Bulgarian lev, fractionalUnitNameSingular, stotinka]
-
A.
fractionalUnitNameInFrench
Indicates the French-language name used for a fractional unit associated with another quantity or measure.
-
B.
unitFractionalName
chosen
Indicates that one entity is the name or label used to represent a fractional unit of another entity (such as a measurement or quantity).
-
C.
fractionalUnitSymbol
Indicates the symbolic notation used to represent the fractional unit associated with a given quantity or measurement.
-
D.
minorUnitName
Indicates the name assigned to a smaller or subordinate unit within a larger structured entity or system.
-
E.
minorUnitsPerUnit
Indicates the number of smaller sub-units that collectively make up one whole unit in a given measurement or currency system.
- 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_69ab4b79846081909096725374d65ce9 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb32ef74819096ae399d16d4f31d |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd829f1e88190aab1d54f87c69714 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.