Triple
T23806182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Road, Derby |
E589713
|
entity |
| Predicate | hasNearbyRailInfrastructure |
P25143
|
FINISHED |
| Object | railway sidings near Derby station |
—
|
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: railway sidings near Derby station | Statement: [London Road, Derby, hasNearbyRailInfrastructure, railway sidings near Derby station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyRailInfrastructure Context triple: [London Road, Derby, hasNearbyRailInfrastructure, railway sidings near Derby station]
-
A.
hasNearbyRailway
chosen
Indicates that one entity is located close to a railway associated with or relevant to another entity.
-
B.
hasNearbyRailwayStation
Indicates that a railway station is located within a short or convenient distance from the referenced entity.
-
C.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
D.
hasNearbyInfrastructureType
Indicates that an entity is located close to infrastructure of a specified type.
-
E.
connectsToRailStation
Indicates that one entity has a direct link, route, or access connection to a rail station.
- 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_69e25d19fecc8190a5cf39bbb18d5d7f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c75206a88190b6e35da289471c27 |
completed | April 29, 2026, 8:54 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:56 p.m.