Triple
T23553836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DB Class 481 |
E578124
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | DB Regio (for S-Bahn Berlin) |
—
|
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: DB Regio (for S-Bahn Berlin) | Statement: [DB Class 481, operator, DB Regio (for S-Bahn Berlin)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DB Regio (for S-Bahn Berlin) Context triple: [DB Class 481, operator, DB Regio (for S-Bahn Berlin)]
-
A.
DB Netz (for most lines)
DB Netz is the rail infrastructure division of Deutsche Bahn responsible for operating and maintaining most of Germany’s railway network.
-
B.
DB Regio
chosen
DB Regio is a division of Germany’s national railway company that operates most of the country’s regional and local passenger train services.
-
C.
S-Bahn
The S-Bahn is a German urban and suburban rapid transit rail system that connects city centers with surrounding metropolitan regions.
-
D.
S-Bahn Berlin GmbH
S-Bahn Berlin GmbH is the company responsible for operating Berlin’s urban rapid transit S-Bahn rail network.
-
E.
Berlin S-Bahn
The Berlin S-Bahn is a rapid transit railway network serving Berlin and its surrounding areas, integrating suburban and urban rail services across the metropolitan region.
- 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_69e245fa93448190919cb04534560542 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1aed17fc881908b45dcde14790d42 |
completed | April 29, 2026, 7:10 a.m. |
Created at: April 17, 2026, 6:11 p.m.