Triple
T3927766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bern metropolitan area |
E93317
|
entity |
| Predicate | suburbanArea |
P15843
|
FINISHED |
| Object | agglomeration of Bern |
—
|
LITERAL FINISHED |
How this triple was built (2 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: agglomeration of Bern | Statement: [Bern metropolitan area, suburbanArea, agglomeration of Bern]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suburbanArea Context triple: [Bern metropolitan area, suburbanArea, agglomeration of Bern]
-
A.
suburb
Indicates that one place is a residential district or outlying area that is part of or adjacent to a larger city or town.
-
B.
hasSuburbanAreas
chosen
Indicates that a place includes or is associated with surrounding residential suburban districts or neighborhoods.
-
C.
isInSuburbanArea
Indicates that something is located within a suburban area, typically between urban and rural regions.
-
D.
urbanAreaType
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
-
E.
isSuburbanCommunity
Indicates that a community is located in a suburban area, typically characterized by residential neighborhoods situated between urban centers and rural regions.
- F. None of above.
Provenance (3 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. |
| PD | Predicate disambiguation | batch_69aee7609c4081908000ce12ae827c3f |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:23 p.m.