Triple

T2637010
Position Surface form Disambiguated ID Type / Status
Subject Wokingham E59768 entity
Predicate hasNeighbouringSettlement P4647 FINISHED
Object Bracknell E58983 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: Bracknell | Statement: [Wokingham, hasNeighbouringSettlement, Bracknell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bracknell
Context triple: [Wokingham, hasNeighbouringSettlement, Bracknell]
  • A. Bracknell chosen
    Bracknell is a town in the English county of Berkshire, known as a post-war New Town and commercial centre in the Thames Valley.
  • B. Bracknell Forest
    Bracknell Forest is a unitary authority area and borough in Berkshire, South East England, encompassing the town of Bracknell and surrounding communities.
  • C. Slough
    Slough is a large industrial and commercial town in southern England, known for its diverse population and proximity to London and Heathrow Airport.
  • D. Aylesbury
    Aylesbury is a historic market town in southern England that serves as an important commercial and administrative center in Buckinghamshire.
  • E. Beaconsfield
    Beaconsfield is a suburban city on the western part of the Island of Montreal in Quebec, Canada, known for its residential character and waterfront along Lake Saint-Louis.
  • 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_69ab4ac8596c8190b34997e73d9e991c completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8e3190081908ea828fe79569cc9 completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69b636e19cb081909b2e7866a8bb3338 completed March 15, 2026, 4:34 a.m.
Created at: March 6, 2026, 9:50 p.m.