Triple

T5485850
Position Surface form Disambiguated ID Type / Status
Subject The Mask E123578 entity
Predicate starring P1507 FINISHED
Object Cameron Diaz E286405 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: Cameron Diaz | Statement: [The Mask, starring, Cameron Diaz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cameron Diaz
Context triple: [The Mask, starring, Cameron Diaz]
  • A. Cameron Diaz chosen
    Cameron Diaz is an American actress known for her roles in hit films such as "There's Something About Mary," "Charlie's Angels," and "Shrek."
  • B. Jessica Alba
    Jessica Alba is an American actress and businesswoman known for her roles in films like "Fantastic Four" and for founding the consumer goods company The Honest Company.
  • C. Jessica Biel
    Jessica Biel is an American actress and producer known for her roles in the TV series "7th Heaven" and films such as "The Texas Chainsaw Massacre" and "The Illusionist."
  • D. Eva Mendes
    Eva Mendes is an American actress and model known for her roles in films such as "Training Day," "Hitch," and "The Place Beyond the Pines."
  • E. Kate Hudson
    Kate Hudson is an American actress known for her roles in romantic comedies and dramas, including her performance in the 2010 crime film "The Killer Inside Me."
  • 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_69bd4648883481909e9775d43300c5fa completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd92625a50819088133641ed6f25a9 completed March 20, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf48a773f48190b9928a96ae2c17f8 completed March 22, 2026, 1:40 a.m.
Created at: March 20, 2026, 2:10 p.m.