Triple

T13338209
Position Surface form Disambiguated ID Type / Status
Subject Maze Runner: The Death Cure E317752 entity
Predicate starring P1507 FINISHED
Object Kaya Scodelario E704400 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: Kaya Scodelario | Statement: [Maze Runner: The Death Cure, starring, Kaya Scodelario]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaya Scodelario
Context triple: [Maze Runner: The Death Cure, starring, Kaya Scodelario]
  • A. Kaya Scodelario chosen
    Kaya Scodelario is an English actress known for her breakout role in the TV series "Skins" and for starring in major film franchises such as "The Maze Runner" and "Pirates of the Caribbean."
  • B. Katherine Hoult
    Katherine Hoult is known as the spouse of Richard Mather.
  • C. Rosanna Hoult
    Rosanna Hoult is a British actress known for her work in film and television and as the sister of actor Nicholas Hoult.
  • D. Shailene Woodley
    Shailene Woodley is an American actress known for her breakout role in "The Descendants" and for starring in films such as "The Fault in Our Stars" and the "Divergent" series.
  • E. Maria Riva
    Maria Riva is a German-American actress and author best known as the daughter and biographer of film legend Marlene Dietrich.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99d01bf8481908cd3a99e5557b972 completed April 11, 2026, 12:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69f76b9c0c088190ba18b5c631bcc365 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:31 p.m.