Triple
T13084860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fridhemsplan |
E310303
|
entity |
| Predicate | isUrbanNode |
P107964
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Fridhemsplan, isUrbanNode, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanNode Context triple: [Fridhemsplan, isUrbanNode, true]
-
A.
isUrbanDistrict
Indicates that a given district is classified as an urban administrative or residential area rather than a rural one.
-
B.
isUrbanForm
Indicates that an entity represents or exhibits characteristics of an urban built environment or city-like spatial structure.
-
C.
isUrbanNeighborhood
Indicates that a given area functions as a neighborhood located within an urban or city environment.
-
D.
isUrbanRoute
Indicates that a route is located within, passes through, or primarily serves an urban or metropolitan area.
-
E.
isUrbanAreaOfType
Indicates that a given area is classified as belonging to a specific type or category of urban area (e.g., city, town, suburb).
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d981361e8c819099376435aa3a7aa3 |
completed | April 10, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69d9803f6c508190bfadfbc2d00c2c64 |
completed | April 10, 2026, 10:57 p.m. |
| PDg | Predicate description generation | batch_69d98114a6508190b1e8e018bb5a068c |
completed | April 10, 2026, 11 p.m. |
Created at: April 9, 2026, 9:02 p.m.