Triple

T14816168
Position Surface form Disambiguated ID Type / Status
Subject Viktor Tikhonov E348320 entity
Predicate familyName P18 FINISHED
Object Tikhonov
Tikhonov is a Russian surname most prominently associated with figures such as legendary Soviet ice hockey coach Viktor Tikhonov and mathematician Andrey Tikhonov.
 E1122465 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: Tikhonov | Statement: [Viktor Tikhonov, familyName, Tikhonov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tikhonov
Context triple: [Viktor Tikhonov, familyName, Tikhonov]
  • A. Nagaev
    Nagaev is the person after whom Nagaev Bay in Russia was named, likely a historical figure associated with the region’s exploration or development.
  • B. Steklov
    Steklov is a Russian surname most notably associated with mathematician Vladimir Steklov, known for his contributions to mathematical physics and spectral theory.
  • C. Sobol
    Sobol is a line of light commercial vehicles produced by the Russian automotive manufacturer GAZ Group.
  • D. Blaschke
    Blaschke is a German surname most notably associated with Wilhelm Blaschke, a prominent mathematician known for his contributions to differential and convex geometry.
  • E. Novikov
    Novikov is a common Russian surname borne by numerous notable figures in fields such as mathematics, physics, literature, and the military.
  • 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: Tikhonov
Triple: [Viktor Tikhonov, familyName, Tikhonov]
Generated description
Tikhonov is a Russian surname most prominently associated with figures such as legendary Soviet ice hockey coach Viktor Tikhonov and mathematician Andrey Tikhonov.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tikhonov
Target entity description: Tikhonov is a Russian surname most prominently associated with figures such as legendary Soviet ice hockey coach Viktor Tikhonov and mathematician Andrey Tikhonov.
  • A. Nagaev
    Nagaev is the person after whom Nagaev Bay in Russia was named, likely a historical figure associated with the region’s exploration or development.
  • B. Steklov
    Steklov is a Russian surname most notably associated with mathematician Vladimir Steklov, known for his contributions to mathematical physics and spectral theory.
  • C. Sobol
    Sobol is a line of light commercial vehicles produced by the Russian automotive manufacturer GAZ Group.
  • D. Blaschke
    Blaschke is a German surname most notably associated with Wilhelm Blaschke, a prominent mathematician known for his contributions to differential and convex geometry.
  • E. Novikov
    Novikov is a common Russian surname borne by numerous notable figures in fields such as mathematics, physics, literature, and the military.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe2c1ec81908b3dff7a5d0e85d0 completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe3897691c819085ef89480e730723 completed May 8, 2026, 7:25 p.m.
NEDg Description generation batch_69fe5178e8b481909c88ee7db29f037c completed May 8, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_69fe5217512c8190b0cea476f4b95007 completed May 8, 2026, 9:13 p.m.
Created at: April 10, 2026, 1:49 a.m.