Triple

T2620030
Position Surface form Disambiguated ID Type / Status
Subject Bracknell E58983 entity
Predicate postTown P2711 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: [Bracknell, postTown, Bracknell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bracknell
Context triple: [Bracknell, postTown, 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_69ab4ac444dc819099614e534dd6021f completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd897acb481909a976b70304cc30e completed March 7, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69b62788456c8190a484826e5d915d9a completed March 15, 2026, 3:29 a.m.
Created at: March 6, 2026, 9:50 p.m.