Triple
T12580124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frankfurt Taunusanlage station |
E300312
|
entity |
| Predicate | servedByLine |
P1293
|
FINISHED |
| Object | S4 |
E987072
|
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: S4 | Statement: [Frankfurt Taunusanlage station, servedByLine, S4]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: S4 Context triple: [Frankfurt Taunusanlage station, servedByLine, S4]
-
A.
S4
S4 is a commuter rail line of the Nuremberg S-Bahn network serving regional passenger traffic in and around Nuremberg, Germany.
-
B.
S4
S4 is a commuter rail line of the Stuttgart S-Bahn network serving the Stuttgart metropolitan area in Germany.
-
C.
S4
S4 is a line of the Munich S-Bahn rapid transit network that runs through the central trunk route and connects Munich with its surrounding suburbs.
-
D.
S4
S4 is a commuter rail line within Germany’s Rhine-Ruhr S-Bahn network, serving suburban and regional connections across the metropolitan area.
-
E.
S4
chosen
S4 is a commuter rail line of the Rhine-Main S-Bahn network serving the Frankfurt 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_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.