Triple
T36861535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solntsevo metro station |
E910949
|
entity |
| Predicate | usesCurrencyForFares |
P136733
|
FINISHED |
| Object | Russian ruble |
—
|
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: Russian ruble | Statement: [Solntsevo metro station, usesCurrencyForFares, Russian ruble]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCurrencyForFares Context triple: [Solntsevo metro station, usesCurrencyForFares, Russian ruble]
-
A.
hasCurrencyOfFares
chosen
Indicates the currency in which fares or prices for transportation or services are denominated.
-
B.
usesCurrency
Indicates that one entity conducts its financial transactions or values using the monetary unit represented by the other entity.
-
C.
usesCurrentCurrenciesOf
Indicates that one entity adopts and operates with the same official currencies that are currently in use in another entity.
-
D.
usesCurrencyInitially
Indicates that an entity originally adopts or operates with a particular currency at the start of a defined period or process.
-
E.
currencyUsedFor
Indicates that a particular currency is used as the medium of exchange or legal tender for a given entity, such as a country, region, or organization.
- 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_69f76e80f6f0819091cba8e19b269615 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe38be079c8190a240191ac0e73e3a |
completed | May 8, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69fe350344508190930de2218156ca02 |
completed | May 8, 2026, 7:09 p.m. |
Created at: May 3, 2026, 4:13 p.m.