Triple
T6662405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ciudad del Este |
E151507
|
entity |
| Predicate | frequentForeignCurrencies |
P4256
|
FINISHED |
| Object | Brazilian real |
—
|
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: Brazilian real | Statement: [Ciudad del Este, frequentForeignCurrencies, Brazilian real]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentForeignCurrencies Context triple: [Ciudad del Este, frequentForeignCurrencies, Brazilian real]
-
A.
involvesCurrency
chosen
Indicates that the relationship or action includes or pertains to the use, exchange, or specification of a particular currency.
-
B.
currencyType
Indicates the specific kind of monetary unit or currency associated with an entity or transaction.
-
C.
usesCurrency
Indicates that one entity conducts its financial transactions or values using the monetary unit represented by the other entity.
-
D.
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).
-
E.
currencyFamily
Indicates that two currencies belong to the same broader monetary family or classification, typically sharing a common origin, standard, or structural framework.
- 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_69c687f5fac48190a09e4838d9c6b45d |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9d53848190ac75523c157249c6 |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6ad071b0081909b96dd4b93414bd1 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:02 p.m.