Triple
T12580903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rüthen |
E300331
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Langenstraße
Langenstraße is a district or neighborhood within the town of Rüthen in North Rhine-Westphalia, Germany.
|
E1017549
|
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: Langenstraße | Statement: [Rüthen, hasSubdivision, Langenstraße]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Langenstraße Context triple: [Rüthen, hasSubdivision, Langenstraße]
-
A.
Hedderichstraße
Hedderichstraße is a street in Frankfurt am Main, Germany, located in the Sachsenhausen district and connected to the city’s public transport network.
-
B.
Voßstraße
Voßstraße is a street in central Berlin, Germany, historically notable for hosting key government buildings of the German Empire and Nazi era near Potsdamer Platz and the government quarter.
-
C.
Kaiserstraße
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.
-
D.
Golßener Straße
Golßener Straße is a street in Berlin, Germany, located in the Neukölln area near Columbiadamm and the former Tempelhof Airport grounds.
-
E.
Scharnweberstraße
Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
- 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: Langenstraße Triple: [Rüthen, hasSubdivision, Langenstraße]
Generated description
Langenstraße is a district or neighborhood within the town of Rüthen in North Rhine-Westphalia, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Langenstraße Target entity description: Langenstraße is a district or neighborhood within the town of Rüthen in North Rhine-Westphalia, Germany.
-
A.
Hedderichstraße
Hedderichstraße is a street in Frankfurt am Main, Germany, located in the Sachsenhausen district and connected to the city’s public transport network.
-
B.
Voßstraße
Voßstraße is a street in central Berlin, Germany, historically notable for hosting key government buildings of the German Empire and Nazi era near Potsdamer Platz and the government quarter.
-
C.
Kaiserstraße
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.
-
D.
Golßener Straße
Golßener Straße is a street in Berlin, Germany, located in the Neukölln area near Columbiadamm and the former Tempelhof Airport grounds.
-
E.
Scharnweberstraße
Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954b97a508190b6c901c506441dd0 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbb2a1088190974e9736873466d1 |
completed | May 3, 2026, 4:14 a.m. |
| NEDg | Description generation | batch_69f6ce6278e081908864fba1db23ada0 |
completed | May 3, 2026, 4:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6cf547b188190b24c51e06a3b4d3c |
completed | May 3, 2026, 4:30 a.m. |
Created at: April 9, 2026, 5:02 p.m.