Triple
T22218331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kottbusser Tor station |
E549136
|
entity |
| Predicate | servedByLine |
P1293
|
FINISHED |
| Object | U3 |
—
|
NE NERFINISHED |
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: U3 | Statement: [Kottbusser Tor station, servedByLine, U3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: U3 Context triple: [Kottbusser Tor station, servedByLine, U3]
-
A.
U3
U3 is one of the main lines of the Nuremberg U-Bahn rapid transit system in Nuremberg, Germany.
-
B.
U3
chosen
U3 is a line of the Berlin U-Bahn rapid transit system serving several districts in the German capital.
-
C.
U3
U3 is a light rail line of the Stuttgart Stadtbahn network serving various districts within the Stuttgart metropolitan area.
-
D.
U3
U3 is one of the main rapid transit lines of the Frankfurt U-Bahn network, connecting central Frankfurt with its northern suburbs.
-
E.
U3
U3 is a rapid transit line of the Munich U-Bahn system in Germany, serving multiple key districts and connecting important transport hubs across the city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e403d6481909a94d0aaf157f6ef |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b8ddb448190a45f0418d813afd0 |
completed | April 28, 2026, 9:50 p.m. |
Created at: April 16, 2026, 8:37 p.m.