Triple

T97869
Position Surface form Disambiguated ID Type / Status
Subject Silicon Fen E1972 entity
Predicate locatedInRegion P40 FINISHED
Object Cambridgeshire E7729 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: Cambridgeshire | Statement: [Silicon Fen, locatedInRegion, Cambridgeshire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cambridgeshire
Context triple: [Silicon Fen, locatedInRegion, Cambridgeshire]
  • A. Cambridgeshire, England chosen
    Cambridgeshire, England is a historic county in eastern England known for its rural landscapes and as the home of the prestigious University of Cambridge.
  • B. Oxfordshire
    Oxfordshire is a historic county in South East England known for the city of Oxford and its prestigious university, as well as its stately homes and rural landscapes.
  • C. Buckinghamshire
    Buckinghamshire is a ceremonial and non-metropolitan county in South East England, known for its historic towns, Chiltern Hills countryside, and proximity to London.
  • D. Hampshire
    Hampshire is a county on England’s south coast known for its historic cities, naval and military heritage, and mix of rural countryside and coastal areas.
  • E. Cheshire
    Cheshire is a ceremonial and historic county in North West England known for its rural landscapes, affluent towns, and production of Cheshire cheese.
  • 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_69a24d4862f881908cc8b89d3a78031d completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a24feef1b08190bb9525f71cce053e completed Feb. 28, 2026, 2:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2f0b22c9c81909a000e612d6d46e5 completed Feb. 28, 2026, 1:42 p.m.
Created at: Feb. 28, 2026, 2:09 a.m.