Triple
T118459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian lira |
E2393
|
entity |
| Predicate | fixedEuroConversionRate |
P2869
|
FINISHED |
| Object | 1 euro = 1936.27 lire |
—
|
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 euro = 1936.27 lire | Statement: [Italian lira, fixedEuroConversionRate, 1 euro = 1936.27 lire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fixedEuroConversionRate Context triple: [Italian lira, fixedEuroConversionRate, 1 euro = 1936.27 lire]
-
A.
replacedCurrencyRate
chosen
Indicates that one currency exchange rate has been superseded or substituted by another rate in a given context.
-
B.
currency
Indicates that one entity serves as the medium of exchange or monetary unit used by another entity (such as a country, region, or system).
-
C.
usesCurrency
Indicates that one entity conducts its financial transactions or values using the monetary unit represented by the other entity.
-
D.
involvesCurrency
Indicates that the relationship or action includes or pertains to the use, exchange, or specification of a particular currency.
-
E.
replacedCurrency
Indicates that one currency has been superseded and no longer used because another currency has taken its place.
- 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a258e0b11c8190b7b5cf3c354c47ce |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a25646d5088190a057989c32da3a90 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.