Triple
T14405361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U-Bahnhof Seestraße |
E357181
|
entity |
| Predicate | isNorthernTerminusOf |
P3375
|
FINISHED |
| Object | Nord-Süd-Linie U6 |
E308543
|
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: Nord-Süd-Linie U6 | Statement: [U-Bahnhof Seestraße, isNorthernTerminusOf, Nord-Süd-Linie U6]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nord-Süd-Linie U6 Context triple: [U-Bahnhof Seestraße, isNorthernTerminusOf, Nord-Süd-Linie U6]
-
A.
S6 Line
The S6 Line is a rapid transit route within the Nanjing Metro system in Nanjing, China.
-
B.
S7 Line
The S7 Line is a suburban rapid transit line of the Nanjing Metro serving outlying districts to the south of Nanjing, China.
-
C.
U6 line
chosen
The U6 line is a route of the Frankfurt U-Bahn rapid transit system that connects various districts across the city, including central hubs such as Hauptwache.
-
D.
S7 line
The S7 line is a Berlin S-Bahn railway service that runs east–west across the city, connecting key districts and suburbs as part of the German capital’s urban transit network.
-
E.
S7 line
The S7 line is a suburban railway service of the Zürich S-Bahn network that connects the city of Zürich with surrounding municipalities along Lake Zürich.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de908804048190a4fe58afc2e0a5b6 |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5523267081908d972b60b6039528 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:17 a.m.