Triple

T3647676
Position Surface form Disambiguated ID Type / Status
Subject Rebecca Hall E77340 entity
Predicate name P16 FINISHED
Object Rebecca Hall E77340 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: Rebecca Hall | Statement: [Rebecca Hall, name, Rebecca Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rebecca Hall
Context triple: [Rebecca Hall, name, Rebecca Hall]
  • A. Rebecca Hall chosen
    Rebecca Hall is a British-American actress and filmmaker known for her nuanced performances in films such as "Vicky Cristina Barcelona," "The Town," and "Christine."
  • B. Rosamund Pike
    Rosamund Pike is an English actress known for her versatile performances in film and television, including acclaimed roles in movies such as "Gone Girl" and "Pride & Prejudice."
  • C. Andrea Riseborough
    Andrea Riseborough is an English actress known for her versatile performances in independent films and major productions such as "Birdman," "Mandy," and the Oscar-nominated "To Leslie."
  • D. Margot Tennant
    Margot Tennant, later Margot Asquith, was a prominent British socialite, author, and wit who became the influential second wife of Prime Minister H. H. Asquith.
  • E. Michelle Gomez
    Michelle Gomez is a Scottish actress best known for her darkly comedic and villainous roles in television series such as Doctor Who and The Chilling Adventures of Sabrina.
  • 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_69ad85de1b988190a45f8dbfebc806fc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc38aa2388190bf1af926375e2433 completed March 8, 2026, 6:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51c6559c88190a0ae63d0f05d5d75 completed March 14, 2026, 8:29 a.m.
Created at: March 8, 2026, 3:24 p.m.