Triple
T1736158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rue de Dunkerque |
E37922
|
entity |
| Predicate | hasVehicleTrafficLevel |
P4588
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Rue de Dunkerque, hasVehicleTrafficLevel, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVehicleTrafficLevel Context triple: [Rue de Dunkerque, hasVehicleTrafficLevel, high]
-
A.
hasPedestrianTrafficLevel
Indicates the level or intensity of pedestrian traffic associated with a given location or pathway.
-
B.
trafficLevel
chosen
Indicates the degree of congestion or flow intensity present in a transportation network or route at a given time.
-
C.
hasTruckTraffic
Indicates that there is truck-related vehicular movement or flow occurring on or through a specified location or route.
-
D.
hasTrafficControl
Indicates that some form of traffic management or regulation mechanism is present or applied to a given route, intersection, or transportation element.
-
E.
roadTraffic
Indicates the presence, flow, or conditions of vehicles and movement along roads or streets.
- 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_69a8861cc6ac8190ac0b2e31ccf62851 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab5c553e508190b0f511b05e07fa20 |
completed | March 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69aa61c25a648190892de94c997fb983 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.