Triple
T12580126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frankfurt Taunusanlage station |
E300312
|
entity |
| Predicate | servedByLine |
P1293
|
FINISHED |
| Object | S6 |
E983300
|
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: S6 | Statement: [Frankfurt Taunusanlage station, servedByLine, S6]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: S6 Context triple: [Frankfurt Taunusanlage station, servedByLine, S6]
-
A.
S6
S6 is one of the Munich S-Bahn suburban railway lines that connects central Munich with its surrounding regions.
-
B.
S6
S6 is a commuter rail line of the Stuttgart S-Bahn network serving the greater Stuttgart metropolitan area in Germany.
-
C.
S6
chosen
S6 is a line of the Rhine-Main S-Bahn rapid transit network serving the Frankfurt am Main area in Germany.
-
D.
S68
S68 is a regional commuter rail line within Germany’s Rhine-Ruhr S-Bahn network, serving suburban and urban areas in the densely populated Rhine-Ruhr metropolitan region.
-
E.
S62
The S62 is a Staten Island bus route in New York City that connects Castleton Corners with other neighborhoods across the borough.
- 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.