Triple

T4869771
Position Surface form Disambiguated ID Type / Status
Subject Guy Hamilton E109057 entity
Predicate workedWith P398 FINISHED
Object Roger Moore E105584 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: Roger Moore | Statement: [Guy Hamilton, workedWith, Roger Moore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roger Moore
Context triple: [Guy Hamilton, workedWith, Roger Moore]
  • A. Roger Moore chosen
    Roger Moore was an English actor best known for playing James Bond in seven films from 1973 to 1985.
  • B. George Lazenby
    George Lazenby is an Australian actor best known for playing James Bond in the 1969 film "On Her Majesty's Secret Service."
  • C. Timothy Dalton
    Timothy Dalton is a British actor best known for portraying James Bond in the films "The Living Daylights" and "Licence to Kill."
  • D. Robert Vaughn
    Robert Vaughn was an American actor best known for his suave, sophisticated roles in film and television, particularly as Napoleon Solo in the 1960s series "The Man from U.N.C.L.E."
  • E. Sean Connery
    Sean Connery was a Scottish actor best known for originating the role of James Bond on film and for his distinguished career in both mainstream and critically acclaimed cinema.
  • 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_69bd440d96a48190b0c87069adef2af1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d9aec60819090f485757038c2a8 completed March 20, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67ee93c08190b3c5b130f82f4bba completed March 21, 2026, 9:42 a.m.
Created at: March 20, 2026, 1:27 p.m.