Triple

T22163592
Position Surface form Disambiguated ID Type / Status
Subject Sex and Lucia E547731 entity
Predicate distributor P1951 FINISHED
Object Warner Sogefilms 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: Warner Sogefilms | Statement: [Sex and Lucia, distributor, Warner Sogefilms]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warner Sogefilms
Context triple: [Sex and Lucia, distributor, Warner Sogefilms]
  • A. Warner Sogefilms chosen
    Warner Sogefilms is a Spanish film distribution company associated with releasing major domestic and international titles.
  • B. Warner Bros. Entertainment
    Warner Bros. Entertainment is a major American film and television studio and media company known for producing blockbuster franchises and owning prominent entertainment brands such as DC Comics.
  • C. Warnercolor
    Warnercolor was a mid-20th-century color motion picture process developed and used by Warner Bros. for many of its films.
  • D. Warner
    Warner is a common English surname borne by numerous notable individuals across literature, entertainment, sports, and public life.
  • E. Warner
    Warner is a small town located in Muskogee County in the state of Oklahoma, United States.
  • 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_69e11e3c4c5c81908d336165816b12e0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12a2f2f90819080b5bb73a6052c24 completed April 28, 2026, 9:44 p.m.
Created at: April 16, 2026, 8:34 p.m.