Triple
T30924343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SSP |
E787815
|
entity |
| Predicate | fractionalUnitValue |
P32237
|
FINISHED |
| Object | 1/100 of South Sudanese pound |
—
|
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: 1/100 of South Sudanese pound | Statement: [SSP, fractionalUnitValue, 1/100 of South Sudanese pound]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fractionalUnitValue Context triple: [SSP, fractionalUnitValue, 1/100 of South Sudanese pound]
-
A.
fractionalUnitCode
Indicates the code that specifies the fractional unit or sub-division of a primary unit used in a measurement or quantity.
-
B.
fractionalUnitSymbol
Indicates the symbolic notation used to represent the fractional unit associated with a given quantity or measurement.
-
C.
fractionalUnitNameInFrench
Indicates the French-language name used for a fractional unit associated with another quantity or measure.
-
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.
valueRelativeToMainUnit
Indicates how a value is expressed in relation to a primary or reference unit, such as a main measurement or base quantity.
- 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_69f224bfaca88190b9d0dfcc86297fe9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f692b82df881909350359a39daa9ff |
completed | May 3, 2026, 12:11 a.m. |
| PD | Predicate disambiguation | batch_69f68b7ec098819080480998038de940 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:51 p.m.