Triple

T18736089
Position Surface form Disambiguated ID Type / Status
Subject Georgy Shengelaya E458166 entity
Predicate fieldOfWork P3 FINISHED
Object Georgian 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: Georgian cinema | Statement: [Georgy Shengelaya, fieldOfWork, Georgian cinema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Georgian cinema
Context triple: [Georgy Shengelaya, fieldOfWork, Georgian cinema]
  • A. Tulu cinema
    Tulu cinema is the regional film industry that produces movies in the Tulu language, primarily serving audiences in the coastal Karnataka region of India.
  • B. Lenfilm
    Lenfilm is one of Russia’s oldest and most prominent film studios, based in Saint Petersburg and known for producing many classic Soviet-era movies.
  • C. Kartuli Pilmi studio chosen
    Kartuli Pilmi studio was a Georgian film studio known for producing notable Soviet-era Georgian films.
  • D. Soviet film industry
    The Soviet film industry was the state-controlled cinematic system of the USSR, renowned for its influential directors, propagandistic works, and pioneering contributions to world cinema, particularly in montage and socially themed storytelling.
  • E. Ethiopian film industry
    The Ethiopian film industry is the national cinema sector of Ethiopia, producing films primarily in local languages such as Amharic and reflecting the country’s social, cultural, and historical narratives.
  • 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_69d8d394dc308190b6725073f5db324c completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e57689fa508190ad821d361cba9edf completed April 20, 2026, 12:42 a.m.
Created at: April 10, 2026, 11:51 a.m.