Triple

T1869016
Position Surface form Disambiguated ID Type / Status
Subject Jon Ekstrand E34988 entity
Predicate partOf P40 FINISHED
Object Swedish film industry E100278 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: Swedish film industry | Statement: [Jon Ekstrand, partOf, Swedish film industry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swedish film industry
Context triple: [Jon Ekstrand, partOf, Swedish film industry]
  • A. Gothenburg Film Festival
    The Gothenburg Film Festival is Scandinavia’s largest film festival, showcasing a wide range of international and Nordic cinema each year in Gothenburg, Sweden.
  • B. Film i Väst chosen
    Film i Väst is a major Swedish regional film fund and production company known for co-producing numerous acclaimed European and international films.
  • C. Korean film industry
    The Korean film industry is a globally influential cinema sector known for its innovative storytelling, genre-blending films, and major contributions to the Korean Wave (Hallyu).
  • D. Nollywood
    Nollywood is Nigeria’s prolific film industry, renowned as one of the largest movie producers in the world and a major cultural force across Africa.
  • E. Iranian cinema
    Iranian cinema is the national film industry of Iran, internationally acclaimed for its poetic realism, humanistic storytelling, and influential auteurs such as Abbas Kiarostami and Asghar Farhadi.
  • 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_69a88600b2f88190bc09303e68ab517e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb0b7e4548190a3761133fbbb7b81 completed March 7, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1dab2a481909adb0a3132348cee completed March 8, 2026, 7:45 p.m.
Created at: March 4, 2026, 7:34 p.m.