Triple

T1655830
Position Surface form Disambiguated ID Type / Status
Subject Tania Chernova E35796 entity
Predicate portrayedBy P1507 FINISHED
Object Rachel Weisz E30057 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: Rachel Weisz | Statement: [Tania Chernova, portrayedBy, Rachel Weisz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rachel Weisz
Context triple: [Tania Chernova, portrayedBy, Rachel Weisz]
  • A. Rachel Weisz chosen
    Rachel Weisz is an Academy Award–winning British actress known for her versatile performances in films such as "The Constant Gardener," "The Mummy," and "The Favourite."
  • B. Sophie Fiennes
    Sophie Fiennes is a British film director and producer known for her innovative documentaries and collaborations with artists and philosophers.
  • C. Rebecca Hall
    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."
  • D. Rebecca Ferguson
    Rebecca Ferguson is a Swedish actress known for her versatile performances in films such as the Mission: Impossible series, The Greatest Showman, and Dune.
  • E. Helen McCrory
    Helen McCrory was an acclaimed English stage and screen actress known for her powerful performances in works such as "Peaky Blinders," the "Harry Potter" film series, and numerous high-profile theatre productions.
  • 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_69a88606aa808190aa0b421b4271f220 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb4535180819088e3bdaa591dcdbd completed March 7, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69adb5b7247c81909224f04af68c3a5d completed March 8, 2026, 5:45 p.m.
Created at: March 4, 2026, 7:29 p.m.