Triple
T10471844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duplex A86 tunnel |
E246940
|
entity |
| Predicate | heavyGoodsVehiclesAllowed |
P94213
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Duplex A86 tunnel, heavyGoodsVehiclesAllowed, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heavyGoodsVehiclesAllowed Context triple: [Duplex A86 tunnel, heavyGoodsVehiclesAllowed, no]
-
A.
cargoVehicle
Indicates a relationship where a vehicle is used or designated for transporting cargo or goods.
-
B.
vehicleLoadingMethod
Indicates the method or process by which a vehicle is loaded with goods, passengers, or other cargo.
-
C.
announcedGrossVehicleWeightRating
Indicates that an entity has a specified gross vehicle weight rating that has been formally announced or declared.
-
D.
towingCapability
Indicates the maximum load or object weight that one entity is able to pull or tow.
-
E.
associatedVehicleWeightClass
Indicates the weight classification category that is linked or assigned to a particular vehicle.
- F. None of above. chosen
Provenance (4 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5094cec788190a485c5c9e7cd024a |
completed | April 7, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d4fb84bafc8190819757b93620508a |
completed | April 7, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69d4fe058fcc81909428137d9ffd6d90 |
completed | April 7, 2026, 12:52 p.m. |
Created at: April 6, 2026, 12:20 p.m.