Triple
T31909296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurt-Schumacher-Straße |
E814636
|
entity |
| Predicate | typicalZoningAlong |
P194059
|
FINISHED |
| Object | mixed-use |
—
|
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: mixed-use | Statement: [Kurt-Schumacher-Straße, typicalZoningAlong, mixed-use]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalZoningAlong Context triple: [Kurt-Schumacher-Straße, typicalZoningAlong, mixed-use]
-
A.
typicalZones
chosen
Indicates that certain spatial or contextual areas are characteristic or commonly associated with a given entity or situation.
-
B.
zoningCharacter
Indicates how the regulatory or functional nature of a geographic area is defined or classified in terms of land-use zoning.
-
C.
hasZoningTrend
Indicates a relationship where a zoning area or jurisdiction exhibits a particular pattern or direction of change in its zoning characteristics over time.
-
D.
typicalDistricts
Indicates that certain districts are characteristic or representative examples of a larger region, category, or entity.
-
E.
hasZoningRestriction
Indicates that an entity is subject to a specific zoning-related limitation or regulatory constraint.
- 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_69f348f109d88190b5005372c53d2fcd |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379eaa540819095a1c5d9f3513f9b |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:01 a.m.