Triple
T4427766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Thun |
E95249
|
entity |
| Predicate | nearSettlement |
P3883
|
FINISHED |
| Object |
Leissigen
Leissigen is a Swiss village in the canton of Bern, known for its scenic location in the Bernese Oberland on the shores of Lake Thun.
|
E443304
|
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: Leissigen | Statement: [Lake Thun, nearSettlement, Leissigen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leissigen Context triple: [Lake Thun, nearSettlement, Leissigen]
-
A.
Kölzig
Kölzig is the surname of former professional ice hockey goaltender Olie Kolzig, best known for his long NHL career with the Washington Capitals.
-
B.
Lochau
Lochau is a locality in Germany historically noted as the place where the influential Reformation-era prince Frederick the Wise died.
-
C.
Vechigen
Vechigen is a rural municipality in the canton of Bern, Switzerland, known for its scattered settlements and agricultural landscape near the city of Bern.
-
D.
Kremmen
Kremmen is a small town and municipality in the Oberhavel district of the German state of Brandenburg.
-
E.
Eidlitz
Eidlitz is a surname most notably associated with Leopold Eidlitz, a prominent 19th-century American architect.
- 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: Leissigen Triple: [Lake Thun, nearSettlement, Leissigen]
Generated description
Leissigen is a Swiss village in the canton of Bern, known for its scenic location in the Bernese Oberland on the shores of Lake Thun.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Leissigen Target entity description: Leissigen is a Swiss village in the canton of Bern, known for its scenic location in the Bernese Oberland on the shores of Lake Thun.
-
A.
Kölzig
Kölzig is the surname of former professional ice hockey goaltender Olie Kolzig, best known for his long NHL career with the Washington Capitals.
-
B.
Lochau
Lochau is a locality in Germany historically noted as the place where the influential Reformation-era prince Frederick the Wise died.
-
C.
Vechigen
Vechigen is a rural municipality in the canton of Bern, Switzerland, known for its scattered settlements and agricultural landscape near the city of Bern.
-
D.
Kremmen
Kremmen is a small town and municipality in the Oberhavel district of the German state of Brandenburg.
-
E.
Eidlitz
Eidlitz is a surname most notably associated with Leopold Eidlitz, a prominent 19th-century American architect.
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355674d5481908bf2dfd611f3520f |
completed | March 13, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6374ffbd081908c96847ec2d25cee |
completed | March 15, 2026, 4:36 a.m. |
| NEDg | Description generation | batch_69b637c48680819094140c463f1c0b93 |
completed | March 15, 2026, 4:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b6383aecb081908c0dc402b8f4add5 |
completed | March 15, 2026, 4:40 a.m. |
Created at: March 12, 2026, 11:30 p.m.