Triple
T16065005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U-Bahn line U3 |
E389708
|
entity |
| Predicate | connectsAt |
P1139
|
FINISHED |
| Object | Spichernstraße |
—
|
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: Spichernstraße | Statement: [U-Bahn line U3, connectsAt, Spichernstraße]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spichernstraße Context triple: [U-Bahn line U3, connectsAt, Spichernstraße]
-
A.
Spichernstraße
chosen
Spichernstraße is a Berlin U-Bahn station that serves as an interchange point on the city's underground network.
-
B.
Lothringerstraße
Lothringerstraße is a central street in Vienna, Austria, located near major landmarks such as Karlsplatz and the Ringstrasse.
-
C.
Eichhornstraße
Eichhornstraße is a street in central Berlin, Germany, located near Leipziger Platz in the city’s historic and commercial district.
-
D.
Bergmannstraße
Bergmannstraße is a notable street in Berlin, Germany, known for its lively mix of cafés, shops, and historic sites including the Luisenstädtischer Friedhof cemetery.
-
E.
Mauerstraße
Mauerstraße is a street in central Berlin, Germany, historically notable for running along the former course of the Berlin Wall near key government and commercial areas.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837bec688190a77ad347600b6bdc |
completed | April 17, 2026, 12:49 a.m. |
Created at: April 10, 2026, 4:57 a.m.