Triple
T24880930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Llanishen railway station |
E622705
|
entity |
| Predicate | hasRegionalRailBrand |
P99839
|
FINISHED |
| Object | Transport for Wales |
E10845
|
NE 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: Transport for Wales | Statement: [Llanishen railway station, hasRegionalRailBrand, Transport for Wales]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalRailBrand Context triple: [Llanishen railway station, hasRegionalRailBrand, Transport for Wales]
-
A.
hasRegionalTrainService
Indicates that a location or route is served by regional train services connecting it to nearby areas.
-
B.
hasLocalRailOperator
Indicates that a specified rail operator is responsible for providing local or regional rail services within a particular area or network.
-
C.
commuterRailBrand
chosen
Indicates that a commuter rail service operates under or is associated with a specific brand or branding identity.
-
D.
usesRollingStockBrand
Indicates that one entity employs or operates rolling stock manufactured under a specific brand.
-
E.
notableTrainBrand
Indicates that an entity is a well-known or significant brand associated with trains or railway services.
- F. None of above.
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_69e2fac4aa848190b3446a3922cec150 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f6640168948190811bd5f933a87cf5 |
completed | May 2, 2026, 8:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a10331edf3481908fec9fd08fab148a |
completed | May 22, 2026, 10:42 a.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 18, 2026, 5:24 a.m.