Triple

T21108664
Position Surface form Disambiguated ID Type / Status
Subject Mirzya (2016 film) E520118 entity
Predicate productionCompany P490 FINISHED
Object ROMP Pictures 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: ROMP Pictures | Statement: [Mirzya (2016 film), productionCompany, ROMP Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ROMP Pictures
Context triple: [Mirzya (2016 film), productionCompany, ROMP Pictures]
  • A. ROMP Pictures chosen
    ROMP Pictures is an Indian film production company best known for producing acclaimed Hindi films directed by its founder, Rakeysh Omprakash Mehra.
  • B. Fotoromanza
    Fotoromanza is a popular 1984 Italian pop-rock song by singer-songwriter Gianna Nannini that became one of her signature hits.
  • C. Trans-Radial Pictures
    Trans-Radial Pictures is a film production company known for working on projects such as the heist comedy "Logan Lucky."
  • D. Pretty Pictures
    Pretty Pictures is a film production company known for producing feature films such as the drama "News of the World."
  • E. Lin Pictures
    Lin Pictures is an American film and television production company founded by producer Dan Lin, known for projects such as the Sherlock Holmes films and The Lego Movie.
  • 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_69e0b509a318819092fbbcb21d1fe603 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e720ffa998819082db225363ac3b23 completed April 21, 2026, 7:02 a.m.
Created at: April 16, 2026, 2:54 p.m.