Triple
T4008422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Südkreuz station |
E89582
|
entity |
| Predicate | hasService |
P182
|
FINISHED |
| Object | S-Bahn lines S25 |
E380231
|
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: S-Bahn lines S25 | Statement: [Südkreuz station, hasService, S-Bahn lines S25]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: S-Bahn lines S25 Context triple: [Südkreuz station, hasService, S-Bahn lines S25]
-
A.
S-Bahn line S25
chosen
S-Bahn line S25 is a Berlin rapid transit route that connects the northern district of Heiligensee with central and southern parts of the city.
-
B.
S-Bahn line S26
S-Bahn line S26 is a suburban railway service in Berlin’s S-Bahn network that connects northern residential districts like Waidmannslust with central parts of the city.
-
C.
S-Bahn line S1
S-Bahn line S1 is a commuter rail service in the Berlin S-Bahn network that connects central Berlin with its northern and southwestern suburbs.
-
D.
S42 (Berlin S-Bahn line)
S42 is a circular Berlin S-Bahn line running clockwise around the city on the Ringbahn, connecting numerous districts and major interchange stations.
-
E.
S46 (Berlin S-Bahn line)
S46 is a Berlin S-Bahn line that connects the southeastern suburbs with the southwestern parts of the city, running through key interchange stations across the network.
- 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_69aed9585e788190bec2d39deba3750f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa647f80819081180eb267f1cfcc |
completed | March 9, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c6ae0ec819099c229a4cfe926f2 |
completed | March 14, 2026, 11:54 a.m. |
Created at: March 9, 2026, 3:34 p.m.