Triple

T875217
Position Surface form Disambiguated ID Type / Status
Subject Oleksandr Kornienko E18901 entity
Predicate familyName P18 FINISHED
Object Kornienko
Kornienko is a Ukrainian surname most notably borne by Oleksandr Kornienko, a contemporary Ukrainian politician and public figure.
 E115665 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: Kornienko | Statement: [Oleksandr Kornienko, familyName, Kornienko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kornienko
Context triple: [Oleksandr Kornienko, familyName, Kornienko]
  • A. Vasilevsky
    Vasilevsky is a Russian surname most prominently associated with Aleksandr Vasilevsky, a leading Soviet military commander and Marshal of the Soviet Union during World War II.
  • B. Yuri
    Yuri is a common Russian given name, famously borne by Yuri Gagarin, the first human to journey into outer space.
  • C. 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.
  • D. Nikolassee
    Nikolassee is a residential locality in southwestern Berlin known for its lakeside setting, green spaces, and villa-style neighborhoods.
  • E. Novoslobodskaya
    Novoslobodskaya is a Moscow Metro station famed for its distinctive stained-glass panels and ornate, cathedral-like interior design.
  • 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: Kornienko
Triple: [Oleksandr Kornienko, familyName, Kornienko]
Generated description
Kornienko is a Ukrainian surname most notably borne by Oleksandr Kornienko, a contemporary Ukrainian politician and public figure.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kornienko
Target entity description: Kornienko is a Ukrainian surname most notably borne by Oleksandr Kornienko, a contemporary Ukrainian politician and public figure.
  • A. Vasilevsky
    Vasilevsky is a Russian surname most prominently associated with Aleksandr Vasilevsky, a leading Soviet military commander and Marshal of the Soviet Union during World War II.
  • B. Yuri
    Yuri is a common Russian given name, famously borne by Yuri Gagarin, the first human to journey into outer space.
  • C. 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.
  • D. Nikolassee
    Nikolassee is a residential locality in southwestern Berlin known for its lakeside setting, green spaces, and villa-style neighborhoods.
  • E. Novoslobodskaya
    Novoslobodskaya is a Moscow Metro station famed for its distinctive stained-glass panels and ornate, cathedral-like interior design.
  • 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_69a4938db1f081909bcd1ad2713b6096 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4acae12948190923d31966c26a130 completed March 1, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac1cd167188190aa05992376553550 completed March 7, 2026, 12:40 p.m.
NEDg Description generation batch_69ac1d724cc081908296855b3caa5a5f completed March 7, 2026, 12:43 p.m.
NED2 Entity disambiguation (via description) batch_69ac1e04dc6c8190bcf9c4ffacc78aef completed March 7, 2026, 12:45 p.m.
Created at: March 1, 2026, 7:39 p.m.