Triple
T12566947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Westphalia |
E295497
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Beverungen
Beverungen is a small town in western Germany situated along the Weser River, known for its historic architecture and scenic rural surroundings.
|
E1060880
|
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: Beverungen | Statement: [Province of Westphalia, containsSettlement, Beverungen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beverungen Context triple: [Province of Westphalia, containsSettlement, Beverungen]
-
A.
Unterneukirchen
Unterneukirchen is a municipality in the Altötting district of Bavaria, Germany, known for its rural character and location in southeastern Upper Bavaria.
-
B.
Ehringshausen
Ehringshausen is a municipality in the Lahn-Dill district of the German state of Hesse.
-
C.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
-
D.
Willebadessen
Willebadessen is a small town in western Germany, located in the state of North Rhine-Westphalia.
-
E.
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.
- 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: Beverungen Triple: [Province of Westphalia, containsSettlement, Beverungen]
Generated description
Beverungen is a small town in western Germany situated along the Weser River, known for its historic architecture and scenic rural surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Beverungen Target entity description: Beverungen is a small town in western Germany situated along the Weser River, known for its historic architecture and scenic rural surroundings.
-
A.
Unterneukirchen
Unterneukirchen is a municipality in the Altötting district of Bavaria, Germany, known for its rural character and location in southeastern Upper Bavaria.
-
B.
Ehringshausen
Ehringshausen is a municipality in the Lahn-Dill district of the German state of Hesse.
-
C.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
-
D.
Willebadessen
chosen
Willebadessen is a small town in western Germany, located in the state of North Rhine-Westphalia.
-
E.
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.
- F. None of above.
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_69fd466577508190b1926c475b7c49dc |
completed | May 8, 2026, 2:11 a.m. |
| NEDg | Description generation | batch_69fd4768edc881909a0c586b6d9568a3 |
completed | May 8, 2026, 2:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd47eb7db08190a68f60b255073d8d |
completed | May 8, 2026, 2:18 a.m. |
Created at: April 8, 2026, 11:49 p.m.