Triple

T22102461
Position Surface form Disambiguated ID Type / Status
Subject Joy (2015 film) E546203 entity
Predicate cinematography P1953 FINISHED
Object Linus Sandgren 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: Linus Sandgren | Statement: [Joy (2015 film), cinematography, Linus Sandgren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linus Sandgren
Context triple: [Joy (2015 film), cinematography, 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. Kristian Wåhlin
    Kristian Wåhlin is a Swedish artist and musician best known in the metal scene for his distinctive, atmospheric album cover artwork for numerous prominent bands.
  • C. Mikael Andersson
    Mikael Andersson is a Swedish ice hockey player best known for his significant contributions to the Malmö Redhawks organization.
  • D. Daniel Erlandsson
    Daniel Erlandsson is a Swedish heavy metal drummer best known as the longtime drummer of the melodic death metal band Arch Enemy.
  • E. Mattias Larsson
    Mattias Larsson is a Swedish songwriter and producer known for co-writing major pop hits for artists such as Selena Gomez.
  • 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_69e11e378dc08190896d6a51597afd5a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129163b908190b63ace06016f4db8 completed April 28, 2026, 9:39 p.m.
Created at: April 16, 2026, 8:30 p.m.