Triple
T14266193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U9 |
E353649
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Schloßstraße
Schloßstraße is a Berlin U-Bahn station on the U9 line located in the Steglitz district, serving as a key access point to the nearby Schlossstraße shopping area.
|
E1123312
|
NE FINISHED |
How this triple was built (4 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: Schloßstraße | Statement: [U9, hasStation, Schloßstraße]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schloßstraße Context triple: [U9, hasStation, Schloßstraße]
-
A.
Burgenstraße
Burgenstraße is a famous German tourist route known for connecting numerous historic castles and picturesque medieval towns.
-
B.
Kaufingerstraße
Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
-
C.
Scharnweberstraße
Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
-
D.
Rathausstraße
Rathausstraße is a central street in Berlin’s Mitte district, known for running past the historic Rotes Rathaus (Berlin City Hall) near Alexanderplatz.
-
E.
Gerichtstraße
Gerichtstraße is a street in Berlin, Germany, located in the Wedding district and known for its mix of residential buildings, commercial spaces, and cultural venues.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Schloßstraße Triple: [U9, hasStation, Schloßstraße]
Generated description
Schloßstraße is a Berlin U-Bahn station on the U9 line located in the Steglitz district, serving as a key access point to the nearby Schlossstraße shopping area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schloßstraße Target entity description: Schloßstraße is a Berlin U-Bahn station on the U9 line located in the Steglitz district, serving as a key access point to the nearby Schlossstraße shopping area.
-
A.
Burgenstraße
Burgenstraße is a famous German tourist route known for connecting numerous historic castles and picturesque medieval towns.
-
B.
Kaufingerstraße
Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
-
C.
Scharnweberstraße
Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
-
D.
Rathausstraße
Rathausstraße is a central street in Berlin’s Mitte district, known for running past the historic Rotes Rathaus (Berlin City Hall) near Alexanderplatz.
-
E.
Gerichtstraße
Gerichtstraße is a street in Berlin, Germany, located in the Wedding district and known for its mix of residential buildings, commercial spaces, and cultural venues.
- F. None of above. chosen
Provenance (5 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6358c2288190ac1fd26e688a605d |
completed | April 14, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe64e68118819082448393cc141d96 |
completed | May 8, 2026, 10:34 p.m. |
| NEDg | Description generation | batch_69fe664fe96081908ca0923791bd212b |
completed | May 8, 2026, 10:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe66be64808190bab35f07d556d446 |
completed | May 8, 2026, 10:42 p.m. |
Created at: April 10, 2026, 1:09 a.m.