Triple
T7583986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ofoten Line |
E179560
|
entity |
| Predicate | freightOperator |
P34619
|
FINISHED |
| Object | CargoNet |
E537560
|
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: CargoNet | Statement: [Ofoten Line, freightOperator, CargoNet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CargoNet Context triple: [Ofoten Line, freightOperator, CargoNet]
-
A.
CargoNet
chosen
CargoNet is a major Norwegian rail freight company that transports goods across Norway and into neighboring countries using the national railway network.
-
B.
DB Cargo
DB Cargo is the rail freight division of Germany’s national railway company, providing cargo transport and logistics services across Europe.
-
C.
Cargo
Cargo is Rust’s official build and dependency management tool that streamlines compiling code, managing libraries, and distributing Rust packages.
-
D.
Cargo
Cargo is a small rural town in the Central West region of New South Wales, Australia, known for its agricultural surroundings and village community.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c69f327db881909a21ae3b156f8ded |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c701731a288190b53ffc546a2f47d7 |
completed | March 27, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c861812e08819097fd14fe2b8fee13 |
completed | March 28, 2026, 11:17 p.m. |
Created at: March 27, 2026, 3:52 p.m.