Triple
T13084843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fridhemsplan |
E310303
|
entity |
| Predicate | hasTrafficIntersection |
P80729
|
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, hasTrafficIntersection, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrafficIntersection Context triple: [Fridhemsplan, hasTrafficIntersection, true]
-
A.
hasTrafficSignals
Indicates that traffic control signals are present at or associated with a given location or roadway feature.
-
B.
hasTrafficIsland
Indicates the presence of a traffic island separating or organizing lanes or directions of vehicular movement within a roadway.
-
C.
hasTrafficControl
Indicates that some form of traffic management or regulation mechanism is present or applied to a given route, intersection, or transportation element.
-
D.
hasRailwayCrossing
Indicates that a location or route includes a point where a railway line and a road or path intersect, typically at the same level.
-
E.
hasTrafficFeature
chosen
Indicates that an entity possesses or is associated with a specific traffic-related characteristic, element, or infrastructure feature.
- 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_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. |
Created at: April 9, 2026, 9:02 p.m.