Triple
T13489253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S-Bahn line S1 |
E318589
|
entity |
| Predicate | rollingStock |
P1305
|
FINISHED |
| Object | DBAG Class 480 |
E587778
|
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: DBAG Class 480 | Statement: [S-Bahn line S1, rollingStock, DBAG Class 480]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DBAG Class 480 Context triple: [S-Bahn line S1, rollingStock, DBAG Class 480]
-
A.
DBAG Class 480
chosen
The DBAG Class 480 is a series of electric multiple units used primarily for S-Bahn commuter rail services in Berlin, Germany.
-
B.
DBAG Class 483
The DBAG Class 483 is a modern electric multiple unit train type used by Deutsche Bahn for S-Bahn commuter services in Germany.
-
C.
DBAG Class 481
The DBAG Class 481 is a series of electric multiple units used on the Berlin S-Bahn network, known for their lightweight design and role in modernizing urban rail services in the German capital.
-
D.
DBAG Class 484
The DBAG Class 484 is a modern electric multiple unit train used for Berlin S-Bahn commuter services in Germany.
-
E.
Class 57 diesel locomotive
The Class 57 diesel locomotive is a British mainline locomotive type, rebuilt from older Class 47s, widely used for both passenger and freight services including prestigious sleeper and charter trains.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf3cbe2081908c6792362c67c8f1 |
completed | April 12, 2026, 2:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75483a6f88190b3815fb8d97e65e4 |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:43 p.m.