Triple

T8625405
Position Surface form Disambiguated ID Type / Status
Subject Man with a Movie Camera E204268 entity
Predicate productionCompany P490 FINISHED
Object VUFKU
VUFKU was a pioneering Soviet Ukrainian film studio of the 1920s known for producing innovative avant-garde and documentary cinema.
 E747554 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: VUFKU | Statement: [Man with a Movie Camera, productionCompany, VUFKU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VUFKU
Context triple: [Man with a Movie Camera, productionCompany, VUFKU]
  • A. GUF
    GUF is the three-letter ISO 3166-1 alpha-3 country code assigned to French Guiana.
  • B. FÜ
    FÜ is the vehicle registration code used on license plates for the city of Fürth in Bavaria, Germany.
  • C. Kuuvak
    Kuuvak is the traditional Indigenous name, used by local Iñupiat peoples, for the river known in English as the Kobuk River in northwestern Alaska.
  • D. Varekai
    Varekai is a Cirque du Soleil touring circus production known for its fantastical forest setting, acrobatic performances, and imaginative storytelling.
  • E. Engativá
    Engativá is a locality in the northwestern part of Bogotá, Colombia, characterized by dense residential areas, commercial zones, and significant transport infrastructure.
  • 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: VUFKU
Triple: [Man with a Movie Camera, productionCompany, VUFKU]
Generated description
VUFKU was a pioneering Soviet Ukrainian film studio of the 1920s known for producing innovative avant-garde and documentary cinema.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VUFKU
Target entity description: VUFKU was a pioneering Soviet Ukrainian film studio of the 1920s known for producing innovative avant-garde and documentary cinema.
  • A. GUF
    GUF is the three-letter ISO 3166-1 alpha-3 country code assigned to French Guiana.
  • B. FÜ
    FÜ is the vehicle registration code used on license plates for the city of Fürth in Bavaria, Germany.
  • C. Kuuvak
    Kuuvak is the traditional Indigenous name, used by local Iñupiat peoples, for the river known in English as the Kobuk River in northwestern Alaska.
  • D. Varekai
    Varekai is a Cirque du Soleil touring circus production known for its fantastical forest setting, acrobatic performances, and imaginative storytelling.
  • E. Engativá
    Engativá is a locality in the northwestern part of Bogotá, Colombia, characterized by dense residential areas, commercial zones, and significant transport infrastructure.
  • 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_69ca834a4ea0819094970dceb9e389f3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc472a07908190a2368975459543f9 completed March 31, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebbf03c688190a989f16675f6e8a6 completed April 2, 2026, 6:56 p.m.
NEDg Description generation batch_69cebdd3ae908190bc4108b766585cbc completed April 2, 2026, 7:04 p.m.
NED2 Entity disambiguation (via description) batch_69cebf1825008190a97cd2df10f8e406 completed April 2, 2026, 7:10 p.m.
Created at: March 30, 2026, 6:26 p.m.