Triple

T2346199
Position Surface form Disambiguated ID Type / Status
Subject River Lea E45136 entity
Predicate flowsThrough P225 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: [River Lea, flowsThrough, Bedfordshire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bedfordshire
Context triple: [River Lea, flowsThrough, 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_69a88917935081909b755dbf38e81024 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abc6c9396081908abb2b0a229bb046 completed March 7, 2026, 6:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69bdd33296a08190b0d3cd9f7a5374a0 completed March 20, 2026, 11:07 p.m.
Created at: March 4, 2026, 7:52 p.m.