Triple
T7012759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adlershof S-Bahn station |
E162623
|
entity |
| Predicate | servedBy |
P82
|
FINISHED |
| Object | S9 line |
E301855
|
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: S9 line | Statement: [Adlershof S-Bahn station, servedBy, S9 line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: S9 line Context triple: [Adlershof S-Bahn station, servedBy, S9 line]
-
A.
S9 line
The S9 line is a regional commuter rail service within the Zürich S-Bahn network, connecting Zürich with surrounding suburbs and towns.
-
B.
S9 line
chosen
The S9 line is a route of the Rhine-Main S-Bahn network serving the Frankfurt metropolitan area and connecting central Frankfurt with surrounding suburbs and regional destinations.
-
C.
S19 line
The S19 line is a suburban rail service within the Zürich S-Bahn network that connects the city with surrounding regional destinations.
-
D.
S29 line
The S29 line is a regional commuter rail service within the Zürich S-Bahn network, connecting suburban and outlying areas with the greater Zürich region.
-
E.
S8 line
The S8 line is a route of the Rhine-Main S-Bahn network in the Frankfurt region, providing suburban rail service that connects central Frankfurt with surrounding cities and the airport.
- 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_69c6885a127c8190867b059bdccf13ff |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc58b04c8190af4913dbaf43c3d4 |
completed | March 27, 2026, 7:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c775656fe48190a9690f5aaca3ba4c |
completed | March 28, 2026, 6:29 a.m. |
Created at: March 27, 2026, 2:34 p.m.