Triple
T37066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Kingdom |
E732
|
entity |
| Predicate | drivingRegulation |
P250
|
FINISHED |
| Object | left-hand traffic |
—
|
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: left-hand traffic | Statement: [United Kingdom, drivingRegulation, left-hand traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drivingRegulation Context triple: [United Kingdom, drivingRegulation, left-hand traffic]
-
A.
drivesOn
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
B.
hasSpeedLimit
Indicates that a specified maximum allowable speed is imposed on the associated entity or context.
-
C.
drivingSide
chosen
Indicates which side of the road (left or right) vehicles are required to drive on in a given jurisdiction.
-
D.
fareControl
Indicates that an entity is responsible for monitoring, enforcing, or managing payment of fares for access to a service or facility.
-
E.
transportation
Indicates the movement of someone or something from one place to another, typically using a vehicle or transit system.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24bb753f081909cd8b25cfb8e08af |
completed | Feb. 28, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69a24ab4a6908190b6f355415ffe7948 |
completed | Feb. 28, 2026, 1:53 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.