Triple

T20080657
Position Surface form Disambiguated ID Type / Status
Subject The Tree of Blood E499989 entity
Predicate productionCompany P490 FINISHED
Object Mediapro 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: Mediapro | Statement: [The Tree of Blood, productionCompany, Mediapro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mediapro
Context triple: [The Tree of Blood, productionCompany, Mediapro]
  • A. Mediapro chosen
    Mediapro is a Spanish multimedia communications group and film and television production company known for producing and co-producing international series, films, and sports broadcasting content.
  • B. Mediasch
    Mediasch is the German name for Mediaș, a historic Transylvanian town in present-day Romania known for its medieval architecture and fortified churches.
  • C. MaMaMedia
    MaMaMedia is an early internet company focused on providing educational, interactive online experiences for children.
  • D. Media Factory
    Media Factory is a creative and digital media hub at the University of Central Lancashire that provides specialized facilities and resources for media, arts, and design students and professionals.
  • E. Telemedia
    Telemedia was a Canadian media company that owned and operated radio stations and other broadcasting assets across the country.
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66557c19c8190b511857490bbd423 completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 3:41 p.m.