Triple

T17105655
Position Surface form Disambiguated ID Type / Status
Subject Okun E415091 entity
Predicate mayReferTo P37 FINISHED
Object Lev Okun E89293 NE FINISHED

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: Lev Okun | Statement: [Okun, mayReferTo, Lev Okun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lev Okun
Context triple: [Okun, mayReferTo, Lev Okun]
  • A. Lev Okun chosen
    Lev Okun was a prominent Soviet theoretical physicist known for his influential work in particle physics and contributions to the understanding of quarks, weak interactions, and the foundations of quantum field theory.
  • B. Sergei Okun
    Sergei Okun is a relatively obscure individual about whom no widely known public information is available.
  • C. Chaim Okun
    Chaim Okun is an individual notable enough to be recognized as a namesake or distinguished bearer of the surname Okun.
  • D. Max Abramovitz
    Max Abramovitz was a prominent American architect known for his modernist designs of major cultural and institutional buildings, including notable performance arts centers and university facilities.
  • E. Morris Okun
    Morris Okun is an American social psychologist known for his research on aging, volunteerism, and the factors that influence well-being in older adults.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dc2683fc81908af2df9012addecb completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a016741fe6c81908ebbb022749915ab completed May 11, 2026, 5:21 a.m.
Created at: April 10, 2026, 5:35 a.m.