Triple
T4913631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Elizabeth Way |
E110293
|
entity |
| Predicate | trafficVolume |
P12939
|
FINISHED |
| Object | one of the busiest highways in Canada |
—
|
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: one of the busiest highways in Canada | Statement: [Queen Elizabeth Way, trafficVolume, one of the busiest highways in Canada]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trafficVolume Context triple: [Queen Elizabeth Way, trafficVolume, one of the busiest highways in Canada]
-
A.
trafficDirection
Indicates the direction in which traffic is intended or allowed to move relative to a given reference point or segment.
-
B.
trafficLevel
Indicates the degree of congestion or flow intensity present in a transportation network or route at a given time.
-
C.
annualTraffic
chosen
Indicates the typical amount or volume of traffic associated with something over the course of a year.
-
D.
cargoTrafficRank
Indicates the relative position of an entity in an ordered list based on the volume or intensity of its cargo traffic.
-
E.
relativeTrafficLevel
Indicates the comparative intensity or volume of traffic between two or more locations, routes, or time periods.
- 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_69bd44132b94819088522d92beaadc78 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e9dc41481908c0c398852e6819c |
completed | March 20, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69bd6c325e188190823836d79934e9bc |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:29 p.m.