Triple

T13971039
Position Surface form Disambiguated ID Type / Status
Subject Viktor Chernomyrdin E336062 entity
Predicate employer P7 FINISHED
Object Gazprom E282855 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: Gazprom | Statement: [Viktor Chernomyrdin, employer, Gazprom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gazprom
Context triple: [Viktor Chernomyrdin, employer, Gazprom]
  • A. Gazprom chosen
    Gazprom is a Russian state-controlled energy giant and one of the world’s largest producers and exporters of natural gas.
  • B. Rosneft
    Rosneft is a major Russian state-controlled oil company and one of the world’s largest publicly traded petroleum producers.
  • C. Lukoil
    Lukoil is one of Russia's largest vertically integrated oil and gas companies, engaged in exploration, production, refining, and marketing of petroleum products worldwide.
  • D. Gazprom Neft
    Gazprom Neft is a major Russian oil company engaged in exploration, production, refining, and marketing of petroleum products.
  • E. Gazprom Transgaz
    Gazprom Transgaz is a major Russian gas transmission company responsible for operating and maintaining large sections of Gazprom’s natural gas pipeline network.
  • 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_69d81c61f3508190aaf2ca0dc0002c59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e8eae40819080dd4bd25c73b6d6 completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1dc838c8190bbcfefd69ea29965 completed May 6, 2026, 8:17 p.m.
Created at: April 9, 2026, 10:18 p.m.