Triple

T21536771
Position Surface form Disambiguated ID Type / Status
Subject Decoding Annie Parker E531368 entity
Predicate starring P1507 FINISHED
Object Maggie Grace 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: Maggie Grace | Statement: [Decoding Annie Parker, starring, Maggie Grace]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maggie Grace
Context triple: [Decoding Annie Parker, starring, Maggie Grace]
  • A. Maggie Grace chosen
    Maggie Grace is an American actress best known for her roles in the TV series "Lost" and the "Taken" film series.
  • B. Dakota Fanning
    Dakota Fanning is an American actress who rose to fame as a child star in films like "I Am Sam" and has since built a diverse career in both mainstream and independent cinema.
  • C. Chloë Grace Moretz
    Chloë Grace Moretz is an American actress known for her versatile performances in films such as "Kick-Ass," "Let Me In," and "If I Stay."
  • D. Haley Bennett
    Haley Bennett is an American actress and singer known for her versatile performances in films such as "The Girl on the Train," "The Magnificent Seven," and "Swallow."
  • E. Olivia DeJonge
    Olivia DeJonge is an Australian actress known for her role as Priscilla Presley in Baz Luhrmann’s 2022 biographical film "Elvis."
  • 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_69e0c45e5b8881908ac18fc2f493b114 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee9d0e5a9c8190894ec3666d3296aa completed April 26, 2026, 11:17 p.m.
Created at: April 16, 2026, 6:27 p.m.