Triple

T8156129
Position Surface form Disambiguated ID Type / Status
Subject Page Eight E190453 entity
Predicate castMember P1668 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: [Page Eight, castMember, Rachel Weisz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rachel Weisz
Context triple: [Page Eight, castMember, 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. Isabelle Carré
    Isabelle Carré is a French actress known for her performances in films such as "Se souvenir des belles choses," for which she won the César Award for Best Actress.
  • 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_69ca82bfeb6481909d07b91b5cf69f59 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb44d8a37481909397b5cc321b94be completed March 31, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde71b7688819096b2d30a37a8a00b completed April 2, 2026, 3:48 a.m.
Created at: March 30, 2026, 5:37 p.m.