Triple

T9549414
Position Surface form Disambiguated ID Type / Status
Subject Arsenal (1929 film) E230379 entity
Predicate follows P134 FINISHED
Object Zvenyhora
Zvenyhora is a 1928 Ukrainian silent film directed by Oleksandr Dovzhenko, renowned for its poetic, avant-garde portrayal of Ukrainian history and folklore.
 E805106 NE FINISHED

How this triple was built (4 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: Zvenyhora | Statement: [Arsenal (1929 film), follows, Zvenyhora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zvenyhora
Context triple: [Arsenal (1929 film), follows, Zvenyhora]
  • A. Volha
    Volha is the Belarusian variant of the female given name Olga.
  • B. Tsitska
    Tsitska is a Georgian white grape variety from the Imereti region, known for producing fresh, high-acidity wines often used in both still and sparkling styles.
  • C. Vyazemsky
    Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
  • D. Kastrychnitskaya
    Kastrychnitskaya is a central Minsk Metro station known for serving the heart of Belarus’s capital near key administrative and cultural landmarks.
  • E. Zhmerynka
    Zhmerynka is a city in central Ukraine known as an important regional railway junction and administrative center.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Zvenyhora
Triple: [Arsenal (1929 film), follows, Zvenyhora]
Generated description
Zvenyhora is a 1928 Ukrainian silent film directed by Oleksandr Dovzhenko, renowned for its poetic, avant-garde portrayal of Ukrainian history and folklore.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zvenyhora
Target entity description: Zvenyhora is a 1928 Ukrainian silent film directed by Oleksandr Dovzhenko, renowned for its poetic, avant-garde portrayal of Ukrainian history and folklore.
  • A. Volha
    Volha is the Belarusian variant of the female given name Olga.
  • B. Tsitska
    Tsitska is a Georgian white grape variety from the Imereti region, known for producing fresh, high-acidity wines often used in both still and sparkling styles.
  • C. Vyazemsky
    Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
  • D. Kastrychnitskaya
    Kastrychnitskaya is a central Minsk Metro station known for serving the heart of Belarus’s capital near key administrative and cultural landmarks.
  • E. Zhmerynka
    Zhmerynka is a city in central Ukraine known as an important regional railway junction and administrative center.
  • F. None of above. chosen

Provenance (5 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_69ca847d3be8819099c9dad2a7e786f1 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99059138819088ae54b26df979cf completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c82c98c8190a4fd6fc3ceb4173d completed April 4, 2026, 5:38 p.m.
NEDg Description generation batch_69d14d23573c8190aeebf2fdac20a332 completed April 4, 2026, 5:40 p.m.
NED2 Entity disambiguation (via description) batch_69d14da4514481908a530b5d77ad832a completed April 4, 2026, 5:43 p.m.
Created at: March 30, 2026, 8:02 p.m.