Triple
T8438350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mechernich |
E199285
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Roggendorf
Roggendorf is a village and district within the town of Mechernich in North Rhine-Westphalia, Germany.
|
E733424
|
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: Roggendorf | Statement: [Mechernich, hasDistrict, Roggendorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roggendorf Context triple: [Mechernich, hasDistrict, Roggendorf]
-
A.
St. Pauli
St. Pauli is a district of Hamburg, Germany, best known for its vibrant nightlife, countercultural scene, and association with the football club FC St. Pauli.
-
B.
Friedrichsdorf
Friedrichsdorf is a town in the German state of Hesse, located north of Frankfurt and known historically for its Huguenot heritage and proximity to the Taunus mountains.
-
C.
Lichterfelde
Lichterfelde is a residential district in southwestern Berlin known for its historic villas, leafy streets, and affluent character.
-
D.
Mladá Boleslav
Mladá Boleslav is a Czech city best known as an important industrial center and the headquarters of the Škoda Auto automobile manufacturer.
-
E.
Ottobrunn
Ottobrunn is a suburban municipality near Munich in Bavaria, Germany, known for its residential character and aerospace industry presence.
- 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: Roggendorf Triple: [Mechernich, hasDistrict, Roggendorf]
Generated description
Roggendorf is a village and district within the town of Mechernich in North Rhine-Westphalia, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Roggendorf Target entity description: Roggendorf is a village and district within the town of Mechernich in North Rhine-Westphalia, Germany.
-
A.
St. Pauli
St. Pauli is a district of Hamburg, Germany, best known for its vibrant nightlife, countercultural scene, and association with the football club FC St. Pauli.
-
B.
Friedrichsdorf
Friedrichsdorf is a town in the German state of Hesse, located north of Frankfurt and known historically for its Huguenot heritage and proximity to the Taunus mountains.
-
C.
Lichterfelde
Lichterfelde is a residential district in southwestern Berlin known for its historic villas, leafy streets, and affluent character.
-
D.
Mladá Boleslav
Mladá Boleslav is a Czech city best known as an important industrial center and the headquarters of the Škoda Auto automobile manufacturer.
-
E.
Ottobrunn
Ottobrunn is a suburban municipality near Munich in Bavaria, Germany, known for its residential character and aerospace industry presence.
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe135657c81908ed8156fbfbef6ec |
completed | March 31, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1d87403c8190b979af4979e43517 |
completed | April 2, 2026, 7:40 a.m. |
| NEDg | Description generation | batch_69ce1f12e1a081909d28b06c520353ef |
completed | April 2, 2026, 7:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce1fb498448190a2737b8895f6bb48 |
completed | April 2, 2026, 7:50 a.m. |
Created at: March 30, 2026, 6:08 p.m.