Triple

T21610185
Position Surface form Disambiguated ID Type / Status
Subject Shteiner E533283 entity
Predicate hasOrthographicVariant P457 FINISHED
Object Shteyner 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: Shteyner | Statement: [Shteiner, hasOrthographicVariant, Shteyner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shteyner
Context triple: [Shteiner, hasOrthographicVariant, Shteyner]
  • A. Shteynberg
    Shteynberg is a variant spelling of the Jewish surname Steinberg, commonly found among Ashkenazi families.
  • B. Shteiner chosen
    Shteiner is an alternative spelling or transliteration of the surname Steiner, which is of German origin and borne by various notable individuals.
  • C. Shtern
    Shtern is a surname most notably associated with Grigory Shtern, a Soviet military commander.
  • D. Ravnitzky
    Ravnitzky is a Jewish family name most notably associated with Yehoshua Ravnitzky, a prominent Hebrew writer, editor, and publisher.
  • E. Plotnitsky
    Plotnitsky is a surname most notably associated with Igor Plotnitsky, a scholar known for his work in literary theory, philosophy, and the study of science and mathematics.
  • 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_69e0c46411108190bba0d4176dffc9f3 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef17e7d1388190922a90cb91ec9fc4 completed April 27, 2026, 8:01 a.m.
Created at: April 16, 2026, 6:33 p.m.