Triple
T31292360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gwynt y Môr |
E797972
|
entity |
| Predicate | hasOnshoreSubstation |
P157754
|
FINISHED |
| Object | St Asaph onshore substation |
—
|
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: St Asaph onshore substation | Statement: [Gwynt y Môr, hasOnshoreSubstation, St Asaph onshore substation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnshoreSubstation Context triple: [Gwynt y Môr, hasOnshoreSubstation, St Asaph onshore substation]
-
A.
hasElectricalSubstation
chosen
Indicates that one entity possesses, contains, or is served by an electrical substation associated with it.
-
B.
onshoreConnectionPoint
Indicates a relationship where an offshore or marine asset is linked to a specific connection point located on land for transfer or integration purposes.
-
C.
hasHVDCConverterStationNearby
Indicates that an entity is located close to a high-voltage direct current (HVDC) converter station.
-
D.
hasNearbyPowerPlants
Indicates that one entity is located close to one or more power plants.
-
E.
hasOutstations
Indicates that an entity maintains or is associated with one or more subsidiary locations or branches situated away from its main base or headquarters.
- 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_69f224dfde288190af313f3c221c857e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f727afd5d88190ad48735cd1b32787 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72737c42c8190a3f781a5e98868ff |
completed | May 3, 2026, 10:45 a.m. |
Created at: April 29, 2026, 9:14 p.m.