Triple
T19093243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SL fare system |
E467340
|
entity |
| Predicate | relatedOrganization |
P37
|
FINISHED |
| Object | Arriva Sverige |
—
|
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: Arriva Sverige | Statement: [SL fare system, relatedOrganization, Arriva Sverige]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arriva Sverige Context triple: [SL fare system, relatedOrganization, Arriva Sverige]
-
A.
Arriva
chosen
Arriva is a major European public transport company that operates bus, coach, train, tram, and waterbus services across multiple countries.
-
B.
Arriva Poland
Arriva Poland is a Polish public transport operator providing bus and rail services as part of the wider Arriva Group’s European operations.
-
C.
Arriva Croatia
Arriva Croatia is a Croatian public transport operator providing regional and intercity bus services as part of the wider European Arriva Group.
-
D.
Arriva Czech Republic
Arriva Czech Republic is a public transport operator in the Czech Republic, providing bus and rail services as part of the international Arriva group.
-
E.
Arriva North West
Arriva North West is a major regional bus operator providing public transport services across North West England.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e34cf5e481908e1f180dacd5602f |
completed | April 20, 2026, 8:26 a.m. |
Created at: April 10, 2026, 12:04 p.m.