Triple

T12588170
Position Surface form Disambiguated ID Type / Status
Subject Winkfield E300521 entity
Predicate postalTown 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: [Winkfield, postalTown, Bracknell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bracknell
Context triple: [Winkfield, postalTown, 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 small unincorporated rural community located in Ringgold County in southern Iowa, United States.
  • 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_69d7bde87b648190bcd0266e9efde098 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954bd5e8c8190a2f233b91682341f completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff677935408190a28af4cd34d82aa4 completed May 9, 2026, 4:57 p.m.
Created at: April 9, 2026, 5:06 p.m.