Triple
T3927730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bern metropolitan area |
E93317
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Ostermundigen
Ostermundigen is a municipality in the canton of Bern, Switzerland, functioning as a suburban community directly adjacent to the city of Bern.
|
E423156
|
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: Ostermundigen | Statement: [Bern metropolitan area, contains, Ostermundigen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ostermundigen Context triple: [Bern metropolitan area, contains, Ostermundigen]
-
A.
Dietingen
Dietingen is a locality that forms one of the subdivisions of the municipality of Blaustein in the German state of Baden-Württemberg.
-
B.
Münklingen
Münklingen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
-
C.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
-
D.
Memmingen
Memmingen is a historic town in the Bavarian region of Germany, known for its well-preserved medieval old town and role as a regional transport hub.
-
E.
Entzheim
Entzheim is a commune in northeastern France, near Strasbourg, best known for hosting Strasbourg Airport.
- 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: Ostermundigen Triple: [Bern metropolitan area, contains, Ostermundigen]
Generated description
Ostermundigen is a municipality in the canton of Bern, Switzerland, functioning as a suburban community directly adjacent to the city of Bern.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ostermundigen Target entity description: Ostermundigen is a municipality in the canton of Bern, Switzerland, functioning as a suburban community directly adjacent to the city of Bern.
-
A.
Dietingen
Dietingen is a locality that forms one of the subdivisions of the municipality of Blaustein in the German state of Baden-Württemberg.
-
B.
Münklingen
Münklingen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
-
C.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
-
D.
Memmingen
Memmingen is a historic town in the Bavarian region of Germany, known for its well-preserved medieval old town and role as a regional transport hub.
-
E.
Entzheim
Entzheim is a commune in northeastern France, near Strasbourg, best known for hosting Strasbourg Airport.
- 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_69aed96bfa1081908f7b30f2c647dee6 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeeda4f9d481908dda1b5a826ab64d |
completed | March 9, 2026, 3:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a82c551c8190a97fdc5a96cf131c |
completed | March 14, 2026, 6:25 p.m. |
| NEDg | Description generation | batch_69b5a8a660bc8190bef754d74ec770b3 |
completed | March 14, 2026, 6:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5a93451388190bd40c55634c8f6f0 |
completed | March 14, 2026, 6:30 p.m. |
Created at: March 9, 2026, 3:23 p.m.