Triple
T20563272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S1 (Munich S-Bahn) |
E504897
|
entity |
| Predicate | rollingStock |
P1305
|
FINISHED |
| Object | DB Class 423 |
—
|
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 Class 423 | Statement: [S1 (Munich S-Bahn), rollingStock, DB Class 423]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DB Class 423 Context triple: [S1 (Munich S-Bahn), rollingStock, DB Class 423]
-
A.
DB Class 423
chosen
DB Class 423 is a series of electric multiple-unit commuter trains widely used in German S-Bahn networks, particularly for high-frequency urban and suburban passenger services.
-
B.
DB Class 422
DB Class 422 is a series of modern electric multiple-unit commuter trains operated by Deutsche Bahn, primarily used on S-Bahn services in Germany.
-
C.
DB Class 425
The DB Class 425 is a series of electric multiple-unit commuter trains operated by Deutsche Bahn, widely used on regional and S-Bahn services in Germany.
-
D.
DB Class 430
The DB Class 430 is a modern electric multiple unit used for suburban and S-Bahn commuter services in Germany.
-
E.
DB Class 484
DB Class 484 is a series of modern electric multiple units built for Berlin’s S-Bahn network, designed to replace older trains and improve urban commuter service.
- 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a7a0a0488190a534050b40ff47da |
completed | April 20, 2026, 10:24 p.m. |
Created at: April 16, 2026, 11:39 a.m.