Triple

T17239644
Position Surface form Disambiguated ID Type / Status
Subject M1 E418454 entity
Predicate passesThroughRegion P3448 FINISHED
Object Bedfordshire E65477 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: Bedfordshire | Statement: [M1, passesThroughRegion, Bedfordshire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bedfordshire
Context triple: [M1, passesThroughRegion, Bedfordshire]
  • A. Bedfordshire chosen
    Bedfordshire is a ceremonial and non-metropolitan county in the East of England, known for its mix of rural countryside, market towns, and the large town of Luton.
  • B. Hertfordshire
    Hertfordshire is a county in southern England known for its historic market towns, countryside, and proximity to London.
  • 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. Buckinghamshire and Hertfordshire
    Buckinghamshire and Hertfordshire are neighboring ceremonial and historic counties in southeastern England, situated northwest and north of London, respectively.
  • E. Northamptonshire
    Northamptonshire is a historic, landlocked county in the East Midlands of England known for its market towns, rural landscapes, and long association with the footwear and leather industries.
  • 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_69d886d8e96081909870bff6c3d0bf09 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e1f385c8190ae44e702923b6f66 completed April 19, 2026, 1:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170df4d1c81909dd05abfd1cfc2ac completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:39 a.m.