Triple
T6725703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brandenburger Tor S-Bahn station |
E153510
|
entity |
| Predicate | servedByLine |
P1293
|
FINISHED |
| Object | S26 |
E143048
|
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: S26 | Statement: [Brandenburger Tor S-Bahn station, servedByLine, S26]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: S26 Context triple: [Brandenburger Tor S-Bahn station, servedByLine, S26]
-
A.
S26
chosen
S26 is a line of the Berlin S-Bahn urban rail network serving various stations across the Berlin metropolitan area.
-
B.
S25
S25 is a commuter rail line of the Berlin S-Bahn network serving various districts across the Berlin metropolitan area.
-
C.
S2
S2 is a line of Berlin's S-Bahn rapid transit network that connects northern and southern suburbs through the city center.
-
D.
S2
S2 is one of the commuter rail lines of the Nuremberg S-Bahn network in Germany, serving suburban and regional routes around the city.
-
E.
S2
S2 is a commuter rail line of the Stuttgart S-Bahn network serving the Stuttgart metropolitan area in Germany.
- 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_69c6880afb988190ad88011b48ecfcba |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d15131f08190aba6c00943c51331 |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c700a5428c81908d4484c3e3734076 |
completed | March 27, 2026, 10:11 p.m. |
Created at: March 27, 2026, 2:08 p.m.