Triple

T8736908
Position Surface form Disambiguated ID Type / Status
Subject Maryport E207408 entity
Predicate near P350 FINISHED
Object Workington E90248 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: Workington | Statement: [Maryport, near, Workington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Workington
Context triple: [Maryport, near, 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. Cockermouth
    Cockermouth is a historic market town in Cumbria, England, known for its Georgian architecture and literary associations, particularly with the poet William Wordsworth.
  • C. Barrow-in-Furness
    Barrow-in-Furness is a coastal industrial town in Cumbria, England, historically known for its shipbuilding and submarine construction.
  • D. Keswick
    Keswick is a suburban community within the town of Georgina in Ontario, Canada, situated along the southern shores of Lake Simcoe.
  • E. Keswick
    Keswick is a historic market town and popular tourist base in England’s Lake District, known for its scenic setting near Derwentwater and surrounding fells.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d45c96081909aa8509064ff3a04 completed March 31, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf42c9140081909f9c10560757c860 completed April 3, 2026, 4:32 a.m.
Created at: March 30, 2026, 6:38 p.m.