Triple

T12455331
Position Surface form Disambiguated ID Type / Status
Subject Olivier Giroud E297641 entity
Predicate givenName P17 FINISHED
Object Olivier E299040 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: Olivier | Statement: [Olivier Giroud, givenName, Olivier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olivier
Context triple: [Olivier Giroud, givenName, Olivier]
  • A. Olivier chosen
    Olivier is a common French given name, notably borne by economist Olivier Blanchard.
  • B. Olivier
    Olivier is a photographic portrait series by Dutch artist Rineke Dijkstra, known for its intimate, psychologically rich depiction of a young French Foreign Legion recruit over time.
  • C. Laurence Olivier
    Laurence Olivier was a renowned 20th-century English actor and director, widely regarded as one of the greatest performers in the history of stage and screen.
  • D. George Borg Olivier
    George Borg Olivier was a Maltese statesman and lawyer who led Malta to independence from the United Kingdom and served as one of its most prominent early prime ministers.
  • E. John Gielgud
    John Gielgud was a distinguished English actor and director renowned for his Shakespearean performances on stage and screen, and as one of the great theatrical knights of the 20th century.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94da2a3cc81908de5a85257627fe2 completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f190c788190adceaab8117d52a6 completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:56 p.m.