Triple

T6766839
Position Surface form Disambiguated ID Type / Status
Subject Frimley Recreation Ground E154742 entity
Predicate locatedIn P40 FINISHED
Object Frimley E28739 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: Frimley | Statement: [Frimley Recreation Ground, locatedIn, Frimley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frimley
Context triple: [Frimley Recreation Ground, locatedIn, Frimley]
  • A. Frimley chosen
    Frimley is a suburban town in southeast England that forms part of the Surrey Heath borough and lies within the county of Surrey.
  • B. Farnham
    Farnham is a historic market town in southern England known for its Georgian streets, medieval castle, and surrounding Surrey countryside.
  • C. Twyford
    Twyford is a village and civil parish in Berkshire, England, known as a commuter settlement between Reading and London.
  • D. Orsett
    Orsett is a village and civil parish in the borough of Thurrock in Essex, England, known for its historic church and traditional village green.
  • E. Limpsfield
    Limpsfield is a historic village and civil parish in Surrey, England, known for its picturesque countryside and traditional English character.
  • 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_69c688109c1c8190added9a221292af0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2303c6881909405f0d6089dbe12 completed March 27, 2026, 6:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c769e417788190a297b277ef0496ff completed March 28, 2026, 5:40 a.m.
Created at: March 27, 2026, 2:12 p.m.