Triple

T7063920
Position Surface form Disambiguated ID Type / Status
Subject Veurne E164295 entity
Predicate hasTwinTown P919 FINISHED
Object Beverley E406105 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: Beverley | Statement: [Veurne, hasTwinTown, Beverley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beverley
Context triple: [Veurne, hasTwinTown, Beverley]
  • A. Beverley chosen
    Beverley is a historic market town and civil parish in the East Riding of Yorkshire, England, known for its impressive Gothic minster and medieval architecture.
  • B. Yorkton
    Yorkton is a small city in southeastern Saskatchewan, Canada, known as a regional hub for agriculture and services.
  • C. Bakewell
    Bakewell is a historic market town in Derbyshire, England, famed for its traditional Bakewell pudding and its picturesque setting in the Peak District.
  • D. Northbourne
    Northbourne is a small village and civil parish in Kent, England, known for its rural character and historic church.
  • E. Banwell
    Banwell is a village and civil parish in North Somerset, England, known for its historic caves and medieval architecture.
  • 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_69c688796c148190adb2f1596f595f22 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e45e80e08190bb1a79a6026d2cd5 completed March 27, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c788ba7af88190aeaf3205255af8ad completed March 28, 2026, 7:52 a.m.
Created at: March 27, 2026, 2:38 p.m.