Triple
T35785960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weiningen (Zurich) |
E1034563
|
entity |
| Predicate | isPartOfAgglomeration |
P101069
|
FINISHED |
| Object | Zurich agglomeration |
—
|
NE NERFINISHED |
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: Zurich agglomeration | Statement: [Weiningen (Zurich), isPartOfAgglomeration, Zurich agglomeration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPartOfAgglomeration Context triple: [Weiningen (Zurich), isPartOfAgglomeration, Zurich agglomeration]
-
A.
hasUrbanAgglomeration
Indicates that an entity includes, is associated with, or is characterized by a specific urban agglomeration (a densely populated urban area and its surrounding zones).
-
B.
isUrbanAgglomerationMember
chosen
Indicates that an entity is part of, or included within, a larger urban agglomeration area.
-
C.
isCoastalAgglomeration
Indicates that an urban agglomeration is located on or directly adjacent to a sea or ocean coastline.
-
D.
isConurbationOf
Indicates that a continuous urban area or metropolitan region is formed by, or results from the merging of, the specified cities or towns.
-
E.
partOfMetropolitanArea
Indicates that one place is included within and belongs to the larger metropolitan area of another place.
- 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_69f76e1575908190aaa306d843b41c14 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ffacdf9f5c8190baef0245edfe87fc |
completed | May 9, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69ffac5e86e08190a1e6da0840a237ad |
completed | May 9, 2026, 9:51 p.m. |
Created at: May 3, 2026, 4:06 p.m.