Triple
T2160213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central African CFA franc |
E47982
|
entity |
| Predicate | fixedExchangeRateToEuro |
P9578
|
FINISHED |
| Object | 655.957 XAF = 1 EUR |
—
|
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: 655.957 XAF = 1 EUR | Statement: [Central African CFA franc, fixedExchangeRateToEuro, 655.957 XAF = 1 EUR]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fixedExchangeRateToEuro Context triple: [Central African CFA franc, fixedExchangeRateToEuro, 655.957 XAF = 1 EUR]
-
A.
fixedConversionRateToEuro
chosen
Indicates that one currency has a fixed, predetermined exchange rate relative to the euro.
-
B.
exchangeRateToPoundSterling
Indicates the rate at which one unit of a given currency can be converted into British pounds sterling.
-
C.
usesExchangeRateRegime
Indicates that one entity adopts or operates under a particular exchange rate regime in conducting its currency or monetary arrangements.
-
D.
currencyProject
Indicates a relationship where a project is associated with, uses, or is denominated in a particular currency.
-
E.
referenceForExchangeRates
Indicates that something serves as the authoritative source or benchmark used to determine or look up exchange rates between currencies.
- 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe8894d481908eda9363fd36fea6 |
completed | March 7, 2026, 5:58 a.m. |
| PD | Predicate disambiguation | batch_69abbd9c90408190b6b65498ca43ce26 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.