Triple

T1049005
Position Surface form Disambiguated ID Type / Status
Subject Windermere E22650 entity
Predicate locatedIn P40 FINISHED
Object Cumbria E14179 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: Cumbria | Statement: [Windermere, locatedIn, Cumbria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cumbria
Context triple: [Windermere, locatedIn, Cumbria]
  • A. Cumbria chosen
    Cumbria is a largely rural county in North West England known for its dramatic landscapes, including most of the Lake District National Park.
  • B. Northumberland
    Northumberland is a historic and largely rural county in northeast England, known for its rugged coastline, medieval castles, and significant Roman heritage.
  • C. Northumberland
    Northumberland is a small rural town in Saratoga County, New York, known for its agricultural character and proximity to the Hudson River.
  • D. Lancashire
    Lancashire is a historic county in North West England known for its role in the Industrial Revolution and major towns such as Lancaster, Preston, and Blackpool.
  • E. Westmorland, England
    Westmorland, England is a historic county in northwestern England known for its rural landscapes and parts of the Lake District.
  • 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8b2c6208190b6fdf3e93b1b1d04 completed March 1, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac53864a20819081fc59e7102a6e00 completed March 7, 2026, 4:34 p.m.
Created at: March 1, 2026, 7:42 p.m.