Triple

T5573757
Position Surface form Disambiguated ID Type / Status
Subject James D'Arcy E146265 entity
Predicate workedWith P398 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: [James D'Arcy, workedWith, Rachel Weisz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rachel Weisz
Context triple: [James D'Arcy, workedWith, 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. Eva Green
    Eva Green is a French actress known for her dark, intense performances in film and television, including prominent roles in projects like "Casino Royale" and "Penny Dreadful."
  • C. Sophie Fiennes
    Sophie Fiennes is a British film director and producer known for her innovative documentaries and collaborations with artists and philosophers.
  • D. 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."
  • E. 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.
  • 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_69c008ffed108190a084602227af6157 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02052dd0481909aba6863831357eb completed March 22, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07d85e478819087502c3927997363 completed March 22, 2026, 11:38 p.m.
Created at: March 22, 2026, 3:37 p.m.