Triple

T18400962
Position Surface form Disambiguated ID Type / Status
Subject Christina Gannett E449991 entity
Predicate relativeByMarriage P7844 FINISHED
Object George Lazenby NE NERFINISHED

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: George Lazenby | Statement: [Christina Gannett, relativeByMarriage, George Lazenby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Lazenby
Context triple: [Christina Gannett, relativeByMarriage, George Lazenby]
  • A. George Lazenby chosen
    George Lazenby is an Australian actor best known for playing James Bond in the 1969 film "On Her Majesty's Secret Service."
  • B. Jethro Lazenby
    Jethro Lazenby was an Australian model, actor, and photographer best known as the son of musician Nick Cave.
  • C. Roger Moore
    Roger Moore was an English actor best known for playing James Bond in seven films from 1973 to 1985.
  • D. Lazenby
    Lazenby is a small village in North Yorkshire, England, situated within the borough of Redcar and Cleveland.
  • E. Sid James
    Sid James was a South African-born British comic actor best known for his roles in the "Carry On" film series and his collaborations with comedian Tony Hancock.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9fab8a8819086a9ddc0871715e0 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e5194f2a8c8190afcd7db23e3795fb completed April 19, 2026, 6:05 p.m.
Created at: April 10, 2026, 10:46 a.m.