Triple

T17567109
Position Surface form Disambiguated ID Type / Status
Subject Georgy Daneliya E427842 entity
Predicate notableWork P4 FINISHED
Object Afonya
Afonya is a 1975 Soviet comedy-drama film directed by Georgy Daneliya that follows the life and misadventures of a wayward plumber confronting his own irresponsibility and loneliness.
 E1275361 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: Afonya | Statement: [Georgy Daneliya, notableWork, Afonya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Afonya
Context triple: [Georgy Daneliya, notableWork, Afonya]
  • A. Adony
    Adony is a small town in central Hungary situated along the Danube River in Fejér County.
  • B. Afantou
    Afantou is a village and seaside resort on the island of Rhodes in Greece, known for its long beach and traditional character.
  • C. Faina
    Faina is a feminine given name, notably borne by the celebrated Soviet actress Faina Ranevskaya.
  • D. Lurya
    Lurya is a variant form of the Jewish surname Luria, historically associated with prominent rabbinic and scholarly families.
  • E. Anif
    Anif is a small Austrian municipality near Salzburg, known for its historic castle and as a residence of notable figures.
  • 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: Afonya
Triple: [Georgy Daneliya, notableWork, Afonya]
Generated description
Afonya is a 1975 Soviet comedy-drama film directed by Georgy Daneliya that follows the life and misadventures of a wayward plumber confronting his own irresponsibility and loneliness.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Afonya
Target entity description: Afonya is a 1975 Soviet comedy-drama film directed by Georgy Daneliya that follows the life and misadventures of a wayward plumber confronting his own irresponsibility and loneliness.
  • A. Adony
    Adony is a small town in central Hungary situated along the Danube River in Fejér County.
  • B. Afantou
    Afantou is a village and seaside resort on the island of Rhodes in Greece, known for its long beach and traditional character.
  • C. Faina
    Faina is a feminine given name, notably borne by the celebrated Soviet actress Faina Ranevskaya.
  • D. Lurya
    Lurya is a variant form of the Jewish surname Luria, historically associated with prominent rabbinic and scholarly families.
  • E. Anif
    Anif is a small Austrian municipality near Salzburg, known for its historic castle and as a residence of notable figures.
  • 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_69d889e0385081908a04b66f4dd4bd0d completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4592da1bc8190968f895e579771ed completed April 19, 2026, 4:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01d29a14288190b5b665c5450b7c18 completed May 11, 2026, 12:59 p.m.
NEDg Description generation batch_6a01d43430d481909b07d8ecc09a185f completed May 11, 2026, 1:05 p.m.
NED2 Entity disambiguation (via description) batch_6a01d4c609fc819089147744317d4be3 completed May 11, 2026, 1:08 p.m.
Created at: April 10, 2026, 5:50 a.m.