Triple
T28259736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UL (Upplands Lokaltrafik) |
E712550
|
entity |
| Predicate | currencyUsedForFares |
P136733
|
FINISHED |
| Object | Swedish krona |
—
|
NE NERFINISHED |
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: Swedish krona | Statement: [UL (Upplands Lokaltrafik), currencyUsedForFares, Swedish krona]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currencyUsedForFares Context triple: [UL (Upplands Lokaltrafik), currencyUsedForFares, Swedish krona]
-
A.
hasCurrencyOfFares
chosen
Indicates the currency in which fares or prices for transportation or services are denominated.
-
B.
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.
-
C.
currencyGiven
Indicates that one entity transfers or provides money or a monetary unit to another entity.
-
D.
currencyType
Indicates the specific kind of monetary unit or currency associated with an entity or transaction.
-
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_69efb5207eb08190827e4c34048030b1 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: April 27, 2026, 11:11 p.m.