Triple
T14266188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U9 |
E353649
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Güntzelstraße
Güntzelstraße is a Berlin U-Bahn station on line U9 located in the Wilmersdorf district of the city.
|
E1119763
|
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: Güntzelstraße | Statement: [U9, hasStation, Güntzelstraße]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Güntzelstraße Context triple: [U9, hasStation, Güntzelstraße]
-
A.
Kleiststraße
Kleiststraße is a street in central Berlin, Germany, located near the Wittenbergplatz area and known for its proximity to major shopping and cultural districts.
-
B.
Siesmayerstraße
Siesmayerstraße is a street in Frankfurt am Main, Germany, known for bordering the historic Palmengarten botanical garden.
-
C.
Grunerstraße
Grunerstraße is a central street in Berlin located near Alexanderplatz, known for carrying heavy traffic through the city’s Mitte district.
-
D.
Glauburgstraße
Glauburgstraße is a station on the Frankfurt U-Bahn network in Frankfurt am Main, Germany.
-
E.
Junghofstraße
Junghofstraße is a street in central Frankfurt am Main, Germany, located near the Taunusanlage area and its major transit connections.
- 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: Güntzelstraße Triple: [U9, hasStation, Güntzelstraße]
Generated description
Güntzelstraße is a Berlin U-Bahn station on line U9 located in the Wilmersdorf district of the city.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Güntzelstraße Target entity description: Güntzelstraße is a Berlin U-Bahn station on line U9 located in the Wilmersdorf district of the city.
-
A.
Kleiststraße
Kleiststraße is a street in central Berlin, Germany, located near the Wittenbergplatz area and known for its proximity to major shopping and cultural districts.
-
B.
Siesmayerstraße
Siesmayerstraße is a street in Frankfurt am Main, Germany, known for bordering the historic Palmengarten botanical garden.
-
C.
Grunerstraße
Grunerstraße is a central street in Berlin located near Alexanderplatz, known for carrying heavy traffic through the city’s Mitte district.
-
D.
Glauburgstraße
Glauburgstraße is a station on the Frankfurt U-Bahn network in Frankfurt am Main, Germany.
-
E.
Junghofstraße
Junghofstraße is a street in central Frankfurt am Main, Germany, located near the Taunusanlage area and its major transit connections.
- 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_69fe249ebd3c81908d8b562845d9ceb1 |
completed | May 8, 2026, 5:59 p.m. |
| NEDg | Description generation | batch_69fe26132f888190b81d072536263a8e |
completed | May 8, 2026, 6:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe266d51608190abde582627a0917b |
completed | May 8, 2026, 6:07 p.m. |
Created at: April 10, 2026, 1:09 a.m.