Triple

T15795392
Position Surface form Disambiguated ID Type / Status
Subject ნიკო ფიროსმანი E382963 entity
Predicate artwork P45579 FINISHED
Object „სუფრა“
„სუფრა“ არის ნიკო ფიროსმანაშვილის ერთ-ერთი ცნობილი ნატურმორტი, რომელიც ქართული სუფრის ტრადიციულ სიუხვასა და ატმოსფეროს ასახავს.
 E1176694 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: „სუფრა“ | Statement: [ნიკო ფიროსმანი, artwork, „სუფრა“]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: „სუფრა“
Context triple: [ნიკო ფიროსმანი, artwork, „სუფრა“]
  • A. SUPO
    SUPO is Finland’s national security and intelligence agency responsible for counterintelligence, counterterrorism, and protecting the country’s internal security.
  • B. SURA
    SURA (Southeastern Universities Research Association) is a consortium of research universities that collaborates to advance scientific research and education, particularly in the southeastern United States.
  • C. Souf
    Souf is a town in Jordan known for its location in the hilly, historically rich region of Jerash in the country’s north.
  • D. Supo
    Supo is Finland’s national security and intelligence agency responsible for counterintelligence, counterterrorism, and protecting the country’s internal security.
  • E. Suvar
    Suvar was an important medieval town and trading center in Volga Bulgaria, serving as one of the region’s key political and economic hubs.
  • 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: „სუფრა“
Triple: [ნიკო ფიროსმანი, artwork, „სუფრა“]
Generated description
„სუფრა“ არის ნიკო ფიროსმანაშვილის ერთ-ერთი ცნობილი ნატურმორტი, რომელიც ქართული სუფრის ტრადიციულ სიუხვასა და ატმოსფეროს ასახავს.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: „სუფრა“
Target entity description: „სუფრა“ არის ნიკო ფიროსმანაშვილის ერთ-ერთი ცნობილი ნატურმორტი, რომელიც ქართული სუფრის ტრადიციულ სიუხვასა და ატმოსფეროს ასახავს.
  • A. SUPO
    SUPO is Finland’s national security and intelligence agency responsible for counterintelligence, counterterrorism, and protecting the country’s internal security.
  • B. SURA
    SURA (Southeastern Universities Research Association) is a consortium of research universities that collaborates to advance scientific research and education, particularly in the southeastern United States.
  • C. Souf
    Souf is a town in Jordan known for its location in the hilly, historically rich region of Jerash in the country’s north.
  • D. Supo
    Supo is Finland’s national security and intelligence agency responsible for counterintelligence, counterterrorism, and protecting the country’s internal security.
  • E. Suvar
    Suvar was an important medieval town and trading center in Volga Bulgaria, serving as one of the region’s key political and economic hubs.
  • 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_69d86da16e188190b89af699f1ed0bfe completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b4dc887081909d682ae153f06d97 completed April 16, 2026, 10:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff90aea81c8190ad8bc0cdedf4b77a completed May 9, 2026, 7:53 p.m.
NEDg Description generation batch_69ff93b24828819092841bc02059995d completed May 9, 2026, 8:06 p.m.
NED2 Entity disambiguation (via description) batch_69ff9435b800819093985b293a541e46 completed May 9, 2026, 8:08 p.m.
Created at: April 10, 2026, 4:48 a.m.