Triple

T708345
Position Surface form Disambiguated ID Type / Status
Subject Cotswolds E14150 entity
Predicate contains P35 FINISHED
Object Chipping Norton E39645 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: Chipping Norton | Statement: [Cotswolds, contains, Chipping Norton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chipping Norton
Context triple: [Cotswolds, contains, Chipping Norton]
  • A. Chipping Norton chosen
    Chipping Norton is a historic market town in Oxfordshire, England, known for its Cotswold stone architecture and rural surroundings.
  • B. Bicester
    Bicester is a historic market town in Oxfordshire, England, best known today for its rapid growth and the popular designer outlet shopping destination Bicester Village.
  • C. Cirencester
    Cirencester is a historic market town in south-central England, renowned for its Roman heritage and Cotswold architecture.
  • D. Didcot
    Didcot is a town in Oxfordshire, England, known historically for its railway junction and nearby power stations.
  • E. Banbury
    Banbury is a historic market town in Oxfordshire, England, known for its medieval cross, canal-side setting, and association with the traditional Banbury cake.
  • 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a548e6dc819090d31ce33493a396 completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7edf6b02c8190995c50a98b4ec326 completed March 4, 2026, 8:31 a.m.
Created at: March 1, 2026, 7:36 p.m.