Triple

T2895301
Position Surface form Disambiguated ID Type / Status
Subject Corpse Bride E63924 entity
Predicate voiceActor P1507 FINISHED
Object Emily Watson E197382 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: Emily Watson | Statement: [Corpse Bride, voiceActor, Emily Watson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emily Watson
Context triple: [Corpse Bride, voiceActor, Emily Watson]
  • A. Emily Watson chosen
    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."
  • B. Sophie Fiennes
    Sophie Fiennes is a British film director and producer known for her innovative documentaries and collaborations with artists and philosophers.
  • C. 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.
  • D. 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."
  • E. Kristin Scott Thomas
    Kristin Scott Thomas is an acclaimed British actress known for her nuanced performances in films such as "The English Patient," "Four Weddings and a Funeral," and "The Horse Whisperer."
  • 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_69ab4c45822c8190830c5f2bb97bcfd0 completed March 6, 2026, 9:51 p.m.
NER Named-entity recognition batch_69abe06509808190b673222b9ae3d599 completed March 7, 2026, 8:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc5925a481908e89f51ad4056708 completed March 11, 2026, 5:23 a.m.
Created at: March 6, 2026, 10:08 p.m.