Triple

T9719628
Position Surface form Disambiguated ID Type / Status
Subject Rothbart E235429 entity
Predicate librettoBy P59320 FINISHED
Object Vasily Geltser E329265 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: Vasily Geltser | Statement: [Rothbart, librettoBy, Vasily Geltser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vasily Geltser
Context triple: [Rothbart, librettoBy, Vasily Geltser]
  • A. Vasily Geltser chosen
    Vasily Geltser was a 19th-century Russian ballet figure known for his work as a librettist and contributor to the development of classical Russian ballet.
  • B. Stepan Chernyak
    Stepan Chernyak was a Soviet military commander best known for leading Red Army forces during World War II.
  • C. Mordechai Bogdanov
    Mordechai Bogdanov is a notable inmate associated with Russia’s infamous Vladimir Central Prison, known for housing prominent and often politically sensitive prisoners.
  • D. Lev Shlosberg
    Lev Shlosberg is a Russian liberal politician, journalist, and human rights advocate known for his opposition to the Kremlin and his work within the Yabloko party.
  • E. Yevgeni Urbansky
    Yevgeni Urbansky was a Soviet film actor known for his intense, emotionally powerful performances in late 1950s and early 1960s cinema.
  • 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_69ca84d0123c819096f9dc3b6abb0881 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9e4022c4819097455f14dd9b1a77 completed April 1, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69d89eedc66c81909076cc7ba35f9da5 completed April 10, 2026, 6:55 a.m.
Created at: March 30, 2026, 8:20 p.m.