Triple
T29314489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M48 motorway |
E743340
|
entity |
| Predicate | hasBridgeDesign |
P154237
|
FINISHED |
| Object | suspension bridge on Severn Bridge |
—
|
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: suspension bridge on Severn Bridge | Statement: [M48 motorway, hasBridgeDesign, suspension bridge on Severn Bridge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBridgeDesign Context triple: [M48 motorway, hasBridgeDesign, suspension bridge on Severn Bridge]
-
A.
hasBridgeOrStructure
Indicates that there exists a bridge or similar structural connection between the related entities.
-
B.
hasBridgeStyle
chosen
Indicates that a bridge is characterized by a particular architectural or structural style.
-
C.
hasBridgeTo
Indicates that one entity is connected to another by a bridge or bridging structure that allows passage or linkage between them.
-
D.
hasBridgeSection
Indicates that one entity includes or is associated with a specific bridge section as a distinct part or component.
-
E.
hasRailBridge
Indicates that one location or structure is connected to another by a bridge specifically designed to carry railway tracks or trains.
- 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_69f0912502c8819087d9e8398ee991a8 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d26ceb08819091c71c001e954936 |
completed | May 3, 2026, 4:43 a.m. |
Created at: April 28, 2026, 1:19 p.m.