Triple
T16225290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rossmarkt |
E393827
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Kaiserstraße |
—
|
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: Kaiserstraße | Statement: [Rossmarkt, connectsTo, Kaiserstraße]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaiserstraße Context triple: [Rossmarkt, connectsTo, Kaiserstraße]
-
A.
Kaiserstraße
chosen
Kaiserstraße is a major shopping and thoroughfare street in central Frankfurt am Main, Germany, known for its historic buildings and proximity to key city landmarks.
-
B.
Kurt-Schumacher-Straße
Kurt-Schumacher-Straße is a major urban street in several German cities, typically serving as an important traffic and commercial artery named after the post-war SPD politician Kurt Schumacher.
-
C.
Karmarschstraße
Karmarschstraße is a central shopping and traffic street in Hanover, Germany, running through the city center near Kröpcke square.
-
D.
Hermannstraße
Hermannstraße is a Berlin railway and U-Bahn station in the Neukölln district that serves as a key interchange point on the city’s Ringbahn network.
-
E.
Sambesistraße
Sambesistraße is a street in Berlin’s Afrikanisches Viertel, a neighborhood known for roads named after African regions, rivers, and countries.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d25f8bc81909aa59b794a528db2 |
completed | April 17, 2026, 2:01 p.m. |
Created at: April 10, 2026, 5:03 a.m.