Triple
T12566916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Westphalia |
E295497
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Ascheberg
Ascheberg is a municipality in western Germany known for its rural character and location within the historic region of Westphalia.
|
E1005343
|
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: Ascheberg | Statement: [Province of Westphalia, containsSettlement, Ascheberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ascheberg Context triple: [Province of Westphalia, containsSettlement, Ascheberg]
-
A.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
-
B.
Havelberg
Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
-
C.
Radeberg
Radeberg is a small town in the German state of Saxony, known for its Radeberger Pilsner brewery and historic town center near Dresden.
-
D.
Gadebusch
Gadebusch is a small historic town in northern Germany known for its medieval architecture and rural surroundings.
-
E.
Dassow
Dassow is a small town in northern Germany’s Mecklenburg-Vorpommern region, near the Baltic Sea coast and the border with Schleswig-Holstein.
- 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: Ascheberg Triple: [Province of Westphalia, containsSettlement, Ascheberg]
Generated description
Ascheberg is a municipality in western Germany known for its rural character and location within the historic region of Westphalia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ascheberg Target entity description: Ascheberg is a municipality in western Germany known for its rural character and location within the historic region of Westphalia.
-
A.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
-
B.
Havelberg
Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
-
C.
Radeberg
Radeberg is a small town in the German state of Saxony, known for its Radeberger Pilsner brewery and historic town center near Dresden.
-
D.
Gadebusch
Gadebusch is a small historic town in northern Germany known for its medieval architecture and rural surroundings.
-
E.
Dassow
Dassow is a small town in northern Germany’s Mecklenburg-Vorpommern region, near the Baltic Sea coast and the border with Schleswig-Holstein.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954a325948190994bcfc9d571a3a8 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ea78dcc819091773d900ad44be6 |
completed | May 2, 2026, 11:54 p.m. |
| NEDg | Description generation | batch_69f6902f138c8190a94a01c1fbb30b57 |
completed | May 3, 2026, midnight |
| NED2 | Entity disambiguation (via description) | batch_69f69138b40881909e9c74d6d922e1f3 |
completed | May 3, 2026, 12:05 a.m. |
Created at: April 8, 2026, 11:49 p.m.