Triple

T3009758
Position Surface form Disambiguated ID Type / Status
Subject American Hustle E81987 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: [American Hustle, cinematographer, Linus Sandgren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linus Sandgren
Context triple: [American Hustle, 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. Erik Renström
    Erik Renström is a Swedish academic and professor who serves as the rector (vice-chancellor) of Lund University.
  • C. Kristian Bäckström
    Kristian Bäckström is a person notable enough to be recognized as a bearer of the Swedish surname Bäckström.
  • D. 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.
  • E. Jonas Alströmer
    Jonas Alströmer was an 18th-century Swedish industrialist and agricultural reformer who played a key role in modernizing Sweden’s economy and scientific institutions.
  • 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_69ad8b1c4de88190a83b7cefaa1f2842 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a4ccbf08190a7580c9e758804d0 completed March 8, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e5f612c8190824deb0813a9f981 completed March 11, 2026, 8:57 a.m.
Created at: March 8, 2026, 3 p.m.