Triple
T35907273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mid Bedfordshire |
E1038504
|
entity |
| Predicate | containsMotorwayOrMajorRoad |
P139729
|
FINISHED |
| Object | M1 motorway corridor |
—
|
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: M1 motorway corridor | Statement: [Mid Bedfordshire, containsMotorwayOrMajorRoad, M1 motorway corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsMotorwayOrMajorRoad Context triple: [Mid Bedfordshire, containsMotorwayOrMajorRoad, M1 motorway corridor]
-
A.
isMajorRoadIn
Indicates that a road is classified as a major road within a specified geographic area or jurisdiction.
-
B.
hasMajorHighway
Indicates that a location or area is served by or directly connected to a major highway route.
-
C.
hasMajorRouteType
Indicates that an entity is associated with a primary classification of transportation route (such as highway, rail line, or other major route type).
-
D.
isMajorTrafficRoute
Indicates that a road or pathway serves as a primary, heavily used route for traffic flow within a transportation network.
-
E.
isMotorwayIn
chosen
Indicates that a motorway is located within or passes through a specified geographic area or administrative region.
- 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_69f76e2259608190bf6788a132e0d139 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a00d820a7788190a8d54625cd87be68 |
completed | May 10, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_6a00d7c5b40c8190b80413238d04e81e |
completed | May 10, 2026, 7:08 p.m. |
Created at: May 3, 2026, 4:07 p.m.