Triple
T16658560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roissybus |
E404797
|
entity |
| Predicate | currencyForFares |
P115600
|
FINISHED |
| Object | euro |
—
|
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: euro | Statement: [Roissybus, currencyForFares, euro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currencyForFares Context triple: [Roissybus, currencyForFares, euro]
-
A.
currencyUsedFor
chosen
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.
-
B.
currencyType
Indicates the specific kind of monetary unit or currency associated with an entity or transaction.
-
C.
currencyServiceType
Indicates the type or category of service associated with a particular currency.
-
D.
currencyFamily
Indicates that two currencies belong to the same broader monetary family or classification, typically sharing a common origin, standard, or structural framework.
-
E.
currencyGiven
Indicates that one entity transfers or provides money or a monetary unit to another entity.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37bfcbb6881909c0419174dd017dc |
completed | April 18, 2026, 12:41 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:18 a.m.