Triple
T16732040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S-Bahn line S2 (Berlin) |
E406614
|
entity |
| Predicate | servesStation |
P839
|
FINISHED |
| Object | Südkreuz station |
E89582
|
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: Südkreuz station | Statement: [S-Bahn line S2 (Berlin), servesStation, Südkreuz station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Südkreuz station Context triple: [S-Bahn line S2 (Berlin), servesStation, Südkreuz station]
-
A.
Südkreuz station
chosen
Südkreuz station is a major Berlin transport hub serving regional, long-distance, and S-Bahn trains in the southern part of the city.
-
B.
Jungfernheide station
Jungfernheide station is a major public transport hub in Berlin’s Charlottenburg-Nord district, serving S-Bahn, U-Bahn, and regional rail lines.
-
C.
Julius-Leber-Brücke station
Julius-Leber-Brücke station is a Berlin S-Bahn railway stop located in the Schöneberg district of Germany’s capital.
-
D.
Ziegelstein station
Ziegelstein station is a stop on the Nuremberg U-Bahn network serving the Ziegelstein district in Nuremberg, Germany.
-
E.
Ostkreuz station
Ostkreuz station is a major railway and S-Bahn interchange in Berlin, Germany, serving as one of the city's busiest public transport hubs.
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e39c362bb88190921fab43d76c3ee8 |
completed | April 18, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d4a94688190aabe56c34e8cc2c3 |
completed | May 10, 2026, 2:59 p.m. |
Created at: April 10, 2026, 5:20 a.m.