Triple

T20196367
Position Surface form Disambiguated ID Type / Status
Subject Ivan Sechenov E493094 entity
Predicate employer P7 FINISHED
Object Novorossiysk University NE NERFINISHED

How this triple was built (2 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: Novorossiysk University | Statement: [Ivan Sechenov, employer, Novorossiysk University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Novorossiysk University
Context triple: [Ivan Sechenov, employer, Novorossiysk University]
  • A. Novorossiysk University chosen
    Novorossiysk University was a higher education institution in the Russian Empire known for educating prominent statesman and reformer Sergei Witte.
  • B. Volgograd State University
    Volgograd State University is a major public higher education and research institution located in the Russian city of Volgograd.
  • C. Rostov State University
    Rostov State University is a Russian higher education institution known for its strong academic programs and as an alma mater of Nobel Prize–winning writer Alexander Solzhenitsyn.
  • D. Kuban State University
    Kuban State University is a major public higher education and research institution located in the city of Krasnodar in southern Russia.
  • E. Crimean Federal University
    Crimean Federal University is a major public higher education institution in Crimea that offers a wide range of academic programs and research opportunities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6268a034819081cbd9ea5a1c9475 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66ad99d50819090ddb7b546c65321 completed April 20, 2026, 6:05 p.m.
Created at: April 11, 2026, 11:37 p.m.