Triple
T20516389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marienplatz |
E503692
|
entity |
| Predicate | connectsWith |
P37
|
FINISHED |
| Object | Kaufingerstraße |
—
|
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: Kaufingerstraße | Statement: [Marienplatz, connectsWith, Kaufingerstraße]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaufingerstraße Context triple: [Marienplatz, connectsWith, Kaufingerstraße]
-
A.
Kaufingerstraße
chosen
Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
-
B.
Feilitzschstraße
Feilitzschstraße is a well-known street in Munich’s Schwabing district, noted for its lively mix of cafés, bars, and cultural venues.
-
C.
Karmarschstraße
Karmarschstraße is a central shopping and traffic street in Hanover, Germany, running through the city center near Kröpcke square.
-
D.
Scharnweberstraße
Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
-
E.
Grunerstraße
Grunerstraße is a central street in Berlin located near Alexanderplatz, known for carrying heavy traffic through the city’s Mitte district.
- 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f41eee481908121e54c7bd691ca |
completed | April 20, 2026, 9:48 p.m. |
Created at: April 16, 2026, 11:36 a.m.