Triple
T16460133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muri bei Bern |
E399784
|
entity |
| Predicate | hasLocality |
P7943
|
FINISHED |
| Object |
Gümligen
Gümligen is a village and suburb in the municipality of Muri bei Bern in the canton of Bern, Switzerland.
|
E1225505
|
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: Gümligen | Statement: [Muri bei Bern, hasLocality, Gümligen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gümligen Context triple: [Muri bei Bern, hasLocality, Gümligen]
-
A.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
-
B.
Zollikon
Zollikon is an affluent suburban municipality on the shores of Lake Zurich, known for its residential character and proximity to the city of Zurich in Switzerland.
-
C.
Hergiswil
Hergiswil is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and its historic glassworks.
-
D.
Adliswil
Adliswil is a municipality in the canton of Zurich, Switzerland, situated in the Sihl Valley just south of the city of Zurich.
-
E.
Würenlingen
Würenlingen is a municipality in the canton of Aargau in northern Switzerland, known for its residential character and proximity to the Aare River and regional transport links.
- 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: Gümligen Triple: [Muri bei Bern, hasLocality, Gümligen]
Generated description
Gümligen is a village and suburb in the municipality of Muri bei Bern in the canton of Bern, Switzerland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gümligen Target entity description: Gümligen is a village and suburb in the municipality of Muri bei Bern in the canton of Bern, Switzerland.
-
A.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
-
B.
Zollikon
Zollikon is an affluent suburban municipality on the shores of Lake Zurich, known for its residential character and proximity to the city of Zurich in Switzerland.
-
C.
Hergiswil
Hergiswil is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and its historic glassworks.
-
D.
Adliswil
Adliswil is a municipality in the canton of Zurich, Switzerland, situated in the Sihl Valley just south of the city of Zurich.
-
E.
Würenlingen
Würenlingen is a municipality in the canton of Aargau in northern Switzerland, known for its residential character and proximity to the Aare River and regional transport links.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d80e66c8190b2b3199efe9cfaa1 |
completed | April 18, 2026, 7:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0084aa47408190abe2ffaab84cdd85 |
completed | May 10, 2026, 1:14 p.m. |
| NEDg | Description generation | batch_6a0085c047f081908d7aa4b8ae5194b9 |
completed | May 10, 2026, 1:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00863e69548190bb8508428c139e05 |
completed | May 10, 2026, 1:21 p.m. |
Created at: April 10, 2026, 5:10 a.m.