Triple
T29781849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Długa Street |
E756136
|
entity |
| Predicate | hasSurfaceUse |
P195536
|
FINISHED |
| Object | outdoor cafes |
—
|
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: outdoor cafes | Statement: [Długa Street, hasSurfaceUse, outdoor cafes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurfaceUse Context triple: [Długa Street, hasSurfaceUse, outdoor cafes]
-
A.
hasSurfaceUseRule
Indicates that there is a rule or constraint governing how a particular surface or area may be used.
-
B.
usesSurface
Indicates that one entity employs or interacts with another entity as a surface or platform for its action or function.
-
C.
hasSurfaceLevel
Indicates that one entity possesses or is characterized by a particular degree or measure of surface level (e.g., depth, detail, or superficiality).
-
D.
hasSurfaceBuilding
Indicates that one entity possesses or is associated with a building located on its surface.
-
E.
hasAlternativeSurface
Indicates that one entity serves as a different or substitute surface option for another entity.
- F. None of above. chosen
Provenance (4 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_69f22451fb748190bbdbab401280affb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fdd92396788190ae1424bc1ae55844 |
completed | May 8, 2026, 12:37 p.m. |
| PD | Predicate disambiguation | batch_69fdd678f40481909a717a2daec83b36 |
completed | May 8, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69fdd922d73c81908ad3faade247ec16 |
completed | May 8, 2026, 12:37 p.m. |
Created at: April 29, 2026, 5:05 p.m.