Triple
T2561259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SKK |
E57244
|
entity |
| Predicate | exchangeRateAtAdoptionOfEuro |
P9578
|
FINISHED |
| Object | 1 EUR = 30.1260 SKK |
—
|
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 EUR = 30.1260 SKK | Statement: [SKK, exchangeRateAtAdoptionOfEuro, 1 EUR = 30.1260 SKK]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exchangeRateAtAdoptionOfEuro Context triple: [SKK, exchangeRateAtAdoptionOfEuro, 1 EUR = 30.1260 SKK]
-
A.
exchangeRateToPapiermark
Indicates the conversion rate or value of one currency in terms of the Papiermark.
-
B.
fixedConversionRateToEuro
chosen
Indicates that one currency has a fixed, predetermined exchange rate relative to the euro.
-
C.
adoptedEuro
Indicates that a country or entity has officially adopted the euro as its legal currency.
-
D.
exchangeRateAtDollarization
Indicates the exchange rate that was in effect at the time a currency or economy underwent dollarization.
-
E.
exchangeRateFixingDate
Indicates the specific date on which an exchange rate is determined or fixed for use in a financial transaction or agreement.
- 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd35c6ee88190b6eaa1841d3e99a4 |
completed | March 7, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69abd0caeb488190b0dd8e48d0f2777d |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.