Triple
T12580127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frankfurt Taunusanlage station |
E300312
|
entity |
| Predicate | servedByLine |
P1293
|
FINISHED |
| Object | S8 |
E987074
|
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: S8 | Statement: [Frankfurt Taunusanlage station, servedByLine, S8]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: S8 Context triple: [Frankfurt Taunusanlage station, servedByLine, S8]
-
A.
S8
S8 is a line of the Berlin S-Bahn urban rail network serving various districts across the Berlin metropolitan area.
-
B.
S8
S8 is a Munich S-Bahn suburban rail service that connects central Munich with its surrounding metropolitan areas.
-
C.
S8
S8 is a regional S-Bahn rail line within Germany’s Rhine-Ruhr metropolitan transit network, connecting key cities and suburbs in the area.
-
D.
S8
chosen
S8 is a regional S-Bahn line in Germany’s Rhine-Main area that connects key cities and suburbs within the Frankfurt metropolitan region.
-
E.
S8 Stock
S8 Stock is a type of London Underground train used on the Metropolitan line, featuring air-conditioned, walk-through carriages designed for longer-distance suburban services.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6559ba5108190b85be540a405eec8 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 9, 2026, 5:01 p.m.