Triple

T21687049
Position Surface form Disambiguated ID Type / Status
Subject Mom E535255 entity
Predicate castMember P1668 FINISHED
Object Anna Faris NE NERFINISHED

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: Anna Faris | Statement: [Mom, castMember, Anna Faris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anna Faris
Context triple: [Mom, castMember, Anna Faris]
  • A. Anna Faris chosen
    Anna Faris is an American actress and comedian best known for her lead role in the Scary Movie film series and her work in both film and television comedy.
  • B. Kristen Schaal
    Kristen Schaal is an American actress, comedian, and voice artist known for her distinctive voice and roles in series like "Flight of the Conchords," "Bob's Burgers," and "The Last Man on Earth."
  • C. Lisa Kudrow
    Lisa Kudrow is an American actress, comedian, writer, and producer best known for playing Phoebe Buffay on the television sitcom "Friends."
  • D. Kathryn Hahn
    Kathryn Hahn is an American actress and comedian known for her versatile roles in film and television, including prominent work in comedies and voice acting.
  • E. Christina Applegate
    Christina Applegate is an American actress and comedian known for her roles in the sitcom "Married... with Children" and numerous film and television comedies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c469b6ec8190aee4cadd1527db91 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef96cc31b8819086ca980521f94501 completed April 27, 2026, 5:03 p.m.
Created at: April 16, 2026, 6:44 p.m.