Triple

T3781061
Position Surface form Disambiguated ID Type / Status
Subject No Time to Die E85416 entity
Predicate cinematographer P1953 FINISHED
Object Linus Sandgren E221279 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: Linus Sandgren | Statement: [No Time to Die, cinematographer, Linus Sandgren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linus Sandgren
Context triple: [No Time to Die, cinematographer, Linus Sandgren]
  • A. Linus Sandgren chosen
    Linus Sandgren is an Academy Award–winning Swedish cinematographer known for his visually distinctive work on films such as La La Land, First Man, and American Hustle.
  • B. Mikael Andersson
    Mikael Andersson is a Swedish ice hockey player best known for his significant contributions to the Malmö Redhawks organization.
  • C. Erik Renström
    Erik Renström is a Swedish academic and professor who serves as the rector (vice-chancellor) of Lund University.
  • D. Kristian Bäckström
    Kristian Bäckström is a person notable enough to be recognized as a bearer of the Swedish surname Bäckström.
  • E. Lars Gustafsson
    Lars Gustafsson was a prominent Swedish novelist, poet, and philosopher known for his intellectually playful, metafictional works and significant influence on late 20th-century Scandinavian literature.
  • 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_69aed937fa8881908208ef3801060826 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee3d98b38819094df9569b549124f completed March 9, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f04353a881908e612a10572eb8c5 completed March 14, 2026, 5:21 a.m.
Created at: March 9, 2026, 3:12 p.m.