Triple
T5313143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutsche Bahn |
E119081
|
entity |
| Predicate | subsidiary |
P258
|
FINISHED |
| Object | DB Regio |
E119083
|
NE 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: DB Regio | Statement: [Deutsche Bahn, subsidiary, DB Regio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DB Regio Context triple: [Deutsche Bahn, subsidiary, DB Regio]
-
A.
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.
-
B.
DB Station&Service
DB Station&Service is a subsidiary of Deutsche Bahn responsible for managing and operating railway stations across Germany.
-
C.
ProRail
ProRail is the Dutch government-owned company responsible for managing and maintaining the national railway infrastructure in the Netherlands.
-
D.
InterRegio
InterRegio is a category of medium- to long-distance passenger trains in several European countries that provides relatively fast regional connections between major cities and regions.
-
E.
RegioExpress
RegioExpress is a category of Swiss regional express trains that provide relatively fast, limited-stop connections between major and medium-sized towns.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd446b57bc8190a513d2e6c40314f3 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8536c06c81908ef8ba8c39b4fa30 |
completed | March 20, 2026, 5:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf1106ef9c8190811f7b70e784c962 |
completed | March 21, 2026, 9:43 p.m. |
Created at: March 20, 2026, 1:54 p.m.