Triple

T9789296
Position Surface form Disambiguated ID Type / Status
Subject About Schmidt E237566 entity
Predicate producer P490 FINISHED
Object Michael Besman E389680 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: Michael Besman | Statement: [About Schmidt, producer, Michael Besman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Besman
Context triple: [About Schmidt, producer, Michael Besman]
  • A. Michael Besman chosen
    Michael Besman is a film producer best known for his work on independent and character-driven movies in Hollywood.
  • B. Valentin Kamensky
    Valentin Kamensky was a Soviet architect best known for co-designing major war memorials, including the Monument to the Heroic Defenders of Leningrad in Saint Petersburg.
  • C. Michael Antonov
    Michael Antonov is a software engineer and entrepreneur best known as a co-founder and early architect of the virtual reality company Oculus VR.
  • D. Roman Malinovsky
    Roman Malinovsky was a prominent early 20th-century Russian revolutionary and Bolshevik leader who infamously served as a secret police informant, betraying his comrades to the Tsarist regime.
  • E. Nikolay Kamensky
    Nikolay Kamensky was a Russian general of the early 19th century known for his prominent role in the Napoleonic-era wars, particularly in campaigns against Sweden and the Ottoman Empire.
  • 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_69ca84da927881909bda80caecad6010 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda214875481909f39e1d4dbac1fdb completed April 1, 2026, 10:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c42c9fe081908145911cad6723c2 completed April 5, 2026, 2:08 a.m.
Created at: March 30, 2026, 8:27 p.m.