Triple

T2422292
Position Surface form Disambiguated ID Type / Status
Subject Keira Knightley E53444 entity
Predicate placeOfBirth P1 FINISHED
Object Teddington, London, England E115402 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: Teddington, London, England | Statement: [Keira Knightley, placeOfBirth, Teddington, London, England]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teddington, London, England
Context triple: [Keira Knightley, placeOfBirth, Teddington, London, England]
  • A. Hendon, London, England
    Hendon, London, England is a suburban district in the London Borough of Barnet known for its aviation history and former airfield.
  • B. Teddington chosen
    Teddington is a suburban town in southwest London, England, known for its riverside location on the Thames and proximity to several royal parks.
  • C. Barnet, London, England
    Barnet is a suburban borough in north London, England, known for its residential character, green spaces, and role as a commuter area for the capital.
  • D. Carshalton, Surrey, England
    Carshalton in Surrey, England, is a suburban town in south London known for its historic village centre, ponds, and green spaces.
  • E. Hammersmith, London, England
    Hammersmith is a vibrant district in West London known for its commercial centers, riverside pubs, and role as a major transport and cultural hub.
  • 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_69ab495c44d48190b7235b23719bc3f6 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc971093481909c8924d58187860c completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf5b1bb8819095920d702c180d3f completed March 9, 2026, 12:38 p.m.
Created at: March 6, 2026, 9:42 p.m.