Triple

T6471945
Position Surface form Disambiguated ID Type / Status
Subject Bishop of Guildford E142373 entity
Predicate basedIn P40 FINISHED
Object Guildford E21568 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: Guildford | Statement: [Bishop of Guildford, basedIn, Guildford]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guildford
Context triple: [Bishop of Guildford, basedIn, Guildford]
  • A. Guildford chosen
    Guildford is a historic market town in southeast England known for its medieval architecture, university, and role as a commercial and cultural hub in the region.
  • B. Farnham
    Farnham is a historic market town in southern England known for its Georgian streets, medieval castle, and surrounding Surrey countryside.
  • C. Basingstoke
    Basingstoke is a large town in Hampshire, England, known as a major commercial and retail centre with significant modern development and transport links.
  • D. Wokingham
    Wokingham is a historic market town in Berkshire, England, known for its traditional town center and role as a commuter hub for nearby Reading and London.
  • E. Camberley
    Camberley is a suburban town in southeast England known for its shopping centre, commuter links to London, and proximity to the Royal Military Academy Sandhurst.
  • 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_69c008d3bf4c8190bcf798c5ba9d6fb3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06a2fd4248190a789bf0301e2860a completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c673f891d08190ad10070bc3a71d76 completed March 27, 2026, 12:11 p.m.
Created at: March 22, 2026, 4:50 p.m.