Triple

T15118641
Position Surface form Disambiguated ID Type / Status
Subject Sandymoor E361106 entity
Predicate hasNeighbouringArea P17964 FINISHED
Object Daresbury E361105 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: Daresbury | Statement: [Sandymoor, hasNeighbouringArea, Daresbury]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daresbury
Context triple: [Sandymoor, hasNeighbouringArea, Daresbury]
  • A. Daresbury chosen
    Daresbury is a village in Cheshire, England, best known as the birthplace of author Lewis Carroll and for its nearby national science and technology facilities.
  • B. Daresbury, Cheshire, England
    Daresbury, Cheshire, England is a small village best known as the birthplace of author and mathematician Lewis Carroll.
  • C. Eddisbury
    Eddisbury is a UK parliamentary constituency in Cheshire, England, represented in the House of Commons.
  • D. Wilmslow
    Wilmslow is an affluent town in Cheshire, England, known for its prosperous residential areas and location within the Greater Manchester commuter belt.
  • E. Chorleywood
    Chorleywood is a commuter village in South East England, known for its green spaces and location on the Metropolitan line within the London commuter belt.
  • 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_69d85a0491ec8190830960be8fafb994 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0059e036c8190959ff3bde8f2356f completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed321d6108190a30b32f176e6d4dc completed May 9, 2026, 6:24 a.m.
Created at: April 10, 2026, 3:06 a.m.