Triple
T21569043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English Welsh & Scottish Railway |
E532235
|
entity |
| Predicate | absorbedInto |
P77
|
FINISHED |
| Object | DB Cargo UK |
—
|
NE NERFINISHED |
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: DB Cargo UK | Statement: [English Welsh & Scottish Railway, absorbedInto, DB Cargo UK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DB Cargo UK Context triple: [English Welsh & Scottish Railway, absorbedInto, DB Cargo UK]
-
A.
DB Cargo
chosen
DB Cargo is the rail freight division of Germany’s national railway company, providing cargo transport and logistics services across Europe.
-
B.
LOT Cargo
LOT Cargo is the air freight and cargo handling division of LOT Polish Airlines, providing logistics and cargo transport services on the carrier’s route network.
-
C.
GB Railfreight
GB Railfreight is a major UK rail freight operating company that provides cargo transport services across the national rail network.
-
D.
CargoNet
CargoNet is a major Norwegian rail freight company that transports goods across Norway and into neighboring countries using the national railway network.
-
E.
Kentish Express
Kentish Express is a local newspaper serving Ashford and the surrounding area in Kent, England.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c460db088190828c64206a450273 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eee9cb9718819094fc95b25df68bd1 |
completed | April 27, 2026, 4:44 a.m. |
Created at: April 16, 2026, 6:30 p.m.