Triple
T15932356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luxembourgish franc |
E386352
|
entity |
| Predicate | exchangeRateFixedAtEuroIntroduction |
P9578
|
FINISHED |
| Object | 1 EUR = 40.3399 LUF |
—
|
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 = 40.3399 LUF | Statement: [Luxembourgish franc, exchangeRateFixedAtEuroIntroduction, 1 EUR = 40.3399 LUF]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exchangeRateFixedAtEuroIntroduction Context triple: [Luxembourgish franc, exchangeRateFixedAtEuroIntroduction, 1 EUR = 40.3399 LUF]
-
A.
cashEuroIntroduction
Indicates the event or process in which euro banknotes and coins are first put into physical circulation as legal tender.
-
B.
fixedConversionRateToEuro
chosen
Indicates that one currency has a fixed, predetermined exchange rate relative to the euro.
-
C.
peggedToEuroSince
Indicates that the value of one currency or financial instrument has been fixed or tightly linked to the euro starting from a specific point in time.
-
D.
fixedExchangeRateToDEM
Indicates that the value of one currency is pegged at a fixed exchange rate relative to the German Deutsche Mark (DEM).
-
E.
exchangeRateToPapiermark
Indicates the conversion rate or value of one currency in terms of the Papiermark.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d37cd88190ab50760f1783e20c |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:52 a.m.