Triple
T12897973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S8 line |
E308542
|
entity |
| Predicate | operatedBy |
P86
|
FINISHED |
| Object | DB Regio Mitte |
E825241
|
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 Mitte | Statement: [S8 line, operatedBy, DB Regio Mitte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DB Regio Mitte Context triple: [S8 line, operatedBy, DB Regio Mitte]
-
A.
DB Regio Mitte
chosen
DB Regio Mitte is a regional division of Deutsche Bahn responsible for operating local and regional passenger train services in central Germany.
-
B.
Berlin U-Bahn
The Berlin U-Bahn is the German capital’s extensive underground rapid transit system, forming a core part of its public transportation network.
-
C.
Berlin Südkreuz
Berlin Südkreuz is a major railway interchange in southern Berlin that serves as a key hub for S-Bahn, regional, and long-distance train services.
-
D.
Berlin Ostkreuz
Berlin Ostkreuz is one of Berlin’s busiest and most important railway hubs, serving as a key interchange point for multiple S-Bahn and regional train lines in the city’s eastern area.
-
E.
Berlin Gesundbrunnen station
Berlin Gesundbrunnen station is a major railway and public transport hub in Berlin, Germany, serving regional, long-distance, and urban transit lines.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9717f3fc48190b61c8f6f36cd0725 |
completed | April 10, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a55f98c08190b8910b1443841fa7 |
completed | May 3, 2026, 1:31 a.m. |
Created at: April 9, 2026, 5:40 p.m.