Triple
T35764071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brunnenstraße |
E1033959
|
entity |
| Predicate | isUrbanAxisBetween |
P57457
|
FINISHED |
| Object | Mitte |
—
|
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: Mitte | Statement: [Brunnenstraße, isUrbanAxisBetween, Mitte]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanAxisBetween Context triple: [Brunnenstraße, isUrbanAxisBetween, Mitte]
-
A.
isUrbanAxisNear
Indicates that one urban axis (such as a main street or corridor) is located in close spatial proximity to another reference feature or axis within an urban area.
-
B.
isUrbanAxis
Indicates that something functions as a primary structural or organizational line within an urban area, such as a main street, corridor, or development spine that shapes the city’s form or activity.
-
C.
isUrbanNode
Indicates that a location or entity functions as an urban center or node within a city or metropolitan network.
-
D.
isUrbanRoute
Indicates that a route is located within, passes through, or primarily serves an urban or metropolitan area.
-
E.
isAxisBetween
chosen
Indicates that one entity serves as a central or reference axis positioned between two other entities in a spatial or structural arrangement.
- 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_69f76e13edd081909101629aa829c4ad |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a1c61e248190ab11908163d6f26c |
completed | May 3, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69f7a070e23881909a233370acb57384 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:06 p.m.