Triple

T7504143
Position Surface form Disambiguated ID Type / Status
Subject Martha Fiennes E177341 entity
Predicate sibling P363 FINISHED
Object Sophie Fiennes E182536 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: Sophie Fiennes | Statement: [Martha Fiennes, sibling, Sophie Fiennes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sophie Fiennes
Context triple: [Martha Fiennes, sibling, Sophie Fiennes]
  • A. Sophie Fiennes chosen
    Sophie Fiennes is a British film director and producer known for her innovative documentaries and collaborations with artists and philosophers.
  • B. Martha Fiennes
    Martha Fiennes is a British film director, writer, and producer best known for her visually distinctive adaptation of "Onegin."
  • C. Emily Watson
    Emily Watson is an acclaimed English actress known for her powerful performances in films such as "Breaking the Waves," "Hilary and Jackie," and "Punch-Drunk Love."
  • 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. Rachel Weisz
    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."
  • 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_69c69f2696688190915a8458f2398211 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5b32c708190bb3a92d0d949304a completed March 27, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84ef2e4588190bedda247ed83bd88 completed March 28, 2026, 9:58 p.m.
Created at: March 27, 2026, 3:44 p.m.