Triple

T13864263
Position Surface form Disambiguated ID Type / Status
Subject Antonov An-2 E333279 entity
Predicate nicknamed P744 FINISHED
Object Annushka
Annushka is the affectionate nickname for the Antonov An-2, a rugged Soviet-era single-engine biplane renowned for its versatility and reliability in harsh conditions.
 E1066176 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: Annushka | Statement: [Antonov An-2, nicknamed, Annushka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Annushka
Context triple: [Antonov An-2, nicknamed, Annushka]
  • A. Anastasie
    Anastasie is the given name of Anastasie de Lafayette, a French noblewoman associated with the influential Lafayette family.
  • B. Nadya
    Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
  • C. Annis
    Annis is a feminine given name of English origin, historically used in the Anglophone world.
  • D. Annelise
    Annelise is the given name of Anni Albers, the influential German-born textile artist and printmaker associated with the Bauhaus and later American modernism.
  • E. Alisa
    Alisa is the birth name of Ayn Rand, the Russian-American novelist and philosopher known for developing Objectivism and writing works such as "Atlas Shrugged" and "The Fountainhead."
  • 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: Annushka
Triple: [Antonov An-2, nicknamed, Annushka]
Generated description
Annushka is the affectionate nickname for the Antonov An-2, a rugged Soviet-era single-engine biplane renowned for its versatility and reliability in harsh conditions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Annushka
Target entity description: Annushka is the affectionate nickname for the Antonov An-2, a rugged Soviet-era single-engine biplane renowned for its versatility and reliability in harsh conditions.
  • A. Anastasie
    Anastasie is the given name of Anastasie de Lafayette, a French noblewoman associated with the influential Lafayette family.
  • B. Nadya
    Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
  • C. Annis
    Annis is a feminine given name of English origin, historically used in the Anglophone world.
  • D. Annelise
    Annelise is the given name of Anni Albers, the influential German-born textile artist and printmaker associated with the Bauhaus and later American modernism.
  • E. Alisa
    Alisa is the birth name of Ayn Rand, the Russian-American novelist and philosopher known for developing Objectivism and writing works such as "Atlas Shrugged" and "The Fountainhead."
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de05c30d9c81908217d41a3b4aaf85 completed April 14, 2026, 9:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c10113288190b799126d934df92a completed May 3, 2026, 9:41 p.m.
NEDg Description generation batch_69f7c1e7efd88190ac07472647da69e7 completed May 3, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_69f7c3396f7c8190987079bf24ac8695 completed May 3, 2026, 9:50 p.m.
Created at: April 9, 2026, 10:14 p.m.