Triple

T18038917
Position Surface form Disambiguated ID Type / Status
Subject Belén Atienza E431587 entity
Predicate employer P7 FINISHED
Object Telecinco Cinema 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: Telecinco Cinema | Statement: [Belén Atienza, employer, Telecinco Cinema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Telecinco Cinema
Context triple: [Belén Atienza, employer, Telecinco Cinema]
  • A. Telecinco Cinema chosen
    Telecinco Cinema is a Spanish film production company known for backing successful and critically acclaimed films, including prominent genre and mainstream titles.
  • B. Atresmedia Cine
    Atresmedia Cine is a Spanish film production company known for producing a wide range of contemporary Spanish-language movies.
  • C. Yara Cinema
    Yara Cinema is a prominent and historic movie theater in Havana, Cuba, known as a cultural landmark and popular gathering place in the Vedado district.
  • D. Eros Cinema
    Eros Cinema is a historic Art Deco movie theater and landmark in Mumbai, India, known for its distinctive architecture and cultural significance.
  • E. Rio Cinema
    Rio Cinema is a historic independent movie theater in the Dalston area of London, known for its art deco architecture and diverse film programming.
  • 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_69d8b9050fb48190890155145deb0a66 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4be3cbe8c8190ba216eeebfc3cbec completed April 19, 2026, 11:36 a.m.
Created at: April 10, 2026, 10:25 a.m.