Triple
T18500926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emmental |
E452062
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Wynigen
Wynigen is a rural municipality in the Emmental region of the Swiss canton of Bern, known for its agricultural landscape and traditional Swiss countryside character.
|
E1327584
|
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: Wynigen | Statement: [Emmental, containsSettlement, Wynigen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wynigen Context triple: [Emmental, containsSettlement, Wynigen]
-
A.
Wustrow
Wustrow is a small town in the Wendland region of Lower Saxony, Germany, known for its rural character and traditional half-timbered architecture.
-
B.
Erwitte
Erwitte is a small town in the German state of North Rhine-Westphalia, known for its historic architecture and location in the Soest district.
-
C.
Wasigny
Wasigny is a small commune in the Ardennes department of northern France, known for its historic medieval architecture and rural character.
-
D.
Wassenberg
Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
-
E.
Wilflingen
Wilflingen is a small village in southern Germany best known as the longtime home of writer Ernst Jünger.
- 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: Wynigen Triple: [Emmental, containsSettlement, Wynigen]
Generated description
Wynigen is a rural municipality in the Emmental region of the Swiss canton of Bern, known for its agricultural landscape and traditional Swiss countryside character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wynigen Target entity description: Wynigen is a rural municipality in the Emmental region of the Swiss canton of Bern, known for its agricultural landscape and traditional Swiss countryside character.
-
A.
Wustrow
Wustrow is a small town in the Wendland region of Lower Saxony, Germany, known for its rural character and traditional half-timbered architecture.
-
B.
Erwitte
Erwitte is a small town in the German state of North Rhine-Westphalia, known for its historic architecture and location in the Soest district.
-
C.
Wasigny
Wasigny is a small commune in the Ardennes department of northern France, known for its historic medieval architecture and rural character.
-
D.
Wassenberg
Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
-
E.
Wilflingen
Wilflingen is a small village in southern Germany best known as the longtime home of writer Ernst Jünger.
- 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e532c43de48190b49b87c1bb591016 |
completed | April 19, 2026, 7:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a047141e8208190b240a11ae3b02ec0 |
completed | May 13, 2026, 12:40 p.m. |
| NEDg | Description generation | batch_6a04738415508190945eec50944d96e9 |
completed | May 13, 2026, 12:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a04746a380c819097df59bdbce0f6f6 |
completed | May 13, 2026, 12:54 p.m. |
Created at: April 10, 2026, 11:36 a.m.