Triple

T13536129
Position Surface form Disambiguated ID Type / Status
Subject Valeriy Lobanovskyi E323265 entity
Predicate givenName P17 FINISHED
Object Valeriy E226539 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: Valeriy | Statement: [Valeriy Lobanovskyi, givenName, Valeriy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valeriy
Context triple: [Valeriy Lobanovskyi, givenName, Valeriy]
  • A. Valeri
    Valeri is the surname of Argentine former professional footballer Diego Valeri, best known as a creative midfielder and Portland Timbers legend in Major League Soccer.
  • B. Vitaly
    Vitaly is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
  • C. Valery chosen
    Valery is a masculine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
  • D. Valentin Varennikov
    Valentin Varennikov was a high-ranking Soviet Army general and political figure who played a prominent role in late Cold War military operations and later became involved in Russian politics.
  • E. Valeriy Heletey
    Valeriy Heletey is a Ukrainian military officer and former Minister of Defence known for his leadership roles during the war in Donbas.
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafbe39948190808062d4eff91841 completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76babfb948190bc028450ddaa0b72 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:44 p.m.