Triple

T7594295
Position Surface form Disambiguated ID Type / Status
Subject Mikhail Anichkov E179816 entity
Predicate hasFamilyName P18 FINISHED
Object Anichkov
Anichkov is a Russian surname most notably associated with figures such as physician and pathologist Mikhail Anichkov.
 E674748 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: Anichkov | Statement: [Mikhail Anichkov, hasFamilyName, Anichkov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Anichkov
Context triple: [Mikhail Anichkov, hasFamilyName, Anichkov]
  • A. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • B. Yura
    Yura is a common Slavic diminutive form of the male given name Yuri (or Yuriy), often used as a familiar or affectionate nickname.
  • C. Gorely
    Gorely is an active stratovolcano complex on Russia’s Kamchatka Peninsula, known for its multiple craters, frequent eruptions, and striking acidic crater lakes.
  • D. Vyazemsky
    Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
  • E. Nagatinskaya
    Nagatinskaya is a Moscow Metro station serving the Serpukhovsko–Timiryazevskaya Line in the Nagatinsky Zaton area of southern Moscow.
  • 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: Anichkov
Triple: [Mikhail Anichkov, hasFamilyName, Anichkov]
Generated description
Anichkov is a Russian surname most notably associated with figures such as physician and pathologist Mikhail Anichkov.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Anichkov
Target entity description: Anichkov is a Russian surname most notably associated with figures such as physician and pathologist Mikhail Anichkov.
  • A. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • B. Yura
    Yura is a common Slavic diminutive form of the male given name Yuri (or Yuriy), often used as a familiar or affectionate nickname.
  • C. Gorely
    Gorely is an active stratovolcano complex on Russia’s Kamchatka Peninsula, known for its multiple craters, frequent eruptions, and striking acidic crater lakes.
  • D. Vyazemsky
    Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
  • E. Nagatinskaya
    Nagatinskaya is a Moscow Metro station serving the Serpukhovsko–Timiryazevskaya Line in the Nagatinsky Zaton area of southern Moscow.
  • 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_69c69f3487ec8190bf7acdf2dd91e6d6 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9bab3a08190a2c36b2c72a1de25 completed March 27, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8619d6f2081908c8b589d4106691f completed March 28, 2026, 11:17 p.m.
NEDg Description generation batch_69c86211e4f88190b38bce6441e33b53 completed March 28, 2026, 11:19 p.m.
NED2 Entity disambiguation (via description) batch_69c862bb95e881909a60608a5279238d completed March 28, 2026, 11:22 p.m.
Created at: March 27, 2026, 3:53 p.m.