Triple
T21778734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A595 |
E537649
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Workington |
—
|
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: Workington | Statement: [A595, connects, Workington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Workington Context triple: [A595, connects, Workington]
-
A.
Workington
chosen
Workington is a coastal town and port on the west coast of England, historically known for its steel and coal industries and situated at the mouth of the River Derwent.
-
B.
Wooler
Wooler is a small market town and gateway to the Cheviot Hills in northern England.
-
C.
Cockermouth
Cockermouth is a historic market town in Cumbria, England, known for its Georgian architecture and literary associations, particularly with the poet William Wordsworth.
-
D.
Seascale
Seascale is a coastal village in Cumbria, England, known for its proximity to the Sellafield nuclear reprocessing and decommissioning site.
-
E.
Barrow-in-Furness
Barrow-in-Furness is a coastal industrial town in Cumbria, England, historically known for its shipbuilding and submarine construction.
- 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_69e0c470759c819094a215757113562b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0462b094c81908207073c278a58fe |
completed | April 28, 2026, 5:31 a.m. |
Created at: April 16, 2026, 6:52 p.m.