Triple
T31452894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hope Street, Glasgow |
E802369
|
entity |
| Predicate | hasVehicularTrafficLevel |
P124688
|
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: [Hope Street, Glasgow, hasVehicularTrafficLevel, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVehicularTrafficLevel Context triple: [Hope Street, Glasgow, hasVehicularTrafficLevel, high]
-
A.
hasLevelOfTraffic
Indicates the degree or intensity of traffic present in or affecting a given entity or location.
-
B.
hasTransitTrafficLevel
Indicates the level or intensity of transit traffic associated with an entity, such as a road segment, route, or area.
-
C.
hasPedestrianTrafficLevel
Indicates the level or intensity of pedestrian traffic associated with a given location or pathway.
-
D.
hasVehicularActivityLevel
chosen
Indicates the degree or intensity of vehicular activity associated with an entity, such as traffic volume or frequency of vehicle use.
-
E.
trafficLevel
Indicates the degree of congestion or flow intensity present in a transportation network or route at a given time.
- 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_69f348c678ac81908a2e950867619061 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6df450014819099d118e5c2d697fa |
completed | May 3, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
Created at: April 30, 2026, 9:14 p.m.