Triple

T10946827
Position Surface form Disambiguated ID Type / Status
Subject Ride Along 2 E258619 entity
Predicate starring P1507 FINISHED
Object Olivia Munn E367216 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: Olivia Munn | Statement: [Ride Along 2, starring, Olivia Munn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olivia Munn
Context triple: [Ride Along 2, starring, Olivia Munn]
  • A. Olivia Munn chosen
    Olivia Munn is an American actress and television personality known for roles in projects like "The Newsroom," "X-Men: Apocalypse," and various comedy and action films.
  • B. Olivia Olson
    Olivia Olson is an American singer and actress best known for her role as Joanna in the film "Love Actually" and for voicing Marceline the Vampire Queen in the animated series "Adventure Time."
  • C. Maggie Siff
    Maggie Siff is an American actress best known for her television roles in series such as Mad Men, Sons of Anarchy, and Billions.
  • D. Radha Mitchell
    Radha Mitchell is an Australian actress known for her versatile performances in independent films and Hollywood productions, including notable roles in dramas, thrillers, and horror films.
  • E. Elisha Cuthbert
    Elisha Cuthbert is a Canadian actress known for her roles in film and television, including prominent parts in series like "24" and various comedy and thriller movies.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770eaaea08190b06e508600d8a305 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c3c885081908edcece772b2e759 completed April 17, 2026, 1:57 p.m.
Created at: April 8, 2026, 9:23 p.m.