Triple

T12257379
Position Surface form Disambiguated ID Type / Status
Subject Oleg Salenko E292135 entity
Predicate club P8194 FINISHED
Object Zenit Leningrad E217583 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: Zenit Leningrad | Statement: [Oleg Salenko, club, Zenit Leningrad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zenit Leningrad
Context triple: [Oleg Salenko, club, Zenit Leningrad]
  • A. Zenit Saint Petersburg chosen
    Zenit Saint Petersburg is a leading Russian professional football club based in Saint Petersburg, known for its domestic league titles, European success, and strong rivalry with Moscow teams.
  • B. CSKA Moscow
    CSKA Moscow is a major Russian sports club best known for its successful football and basketball teams and intense rivalries with other Moscow clubs.
  • C. Dinamo Riga
    Dinamo Riga is a professional ice hockey club based in Riga, Latvia, known for competing in top European and international leagues.
  • D. Basketball Club Dynamo Moscow
    Basketball Club Dynamo Moscow is a Russian professional basketball team based in Moscow, historically known for competing in domestic and European competitions.
  • E. UNICS Kazan
    UNICS Kazan is a professional basketball club from Kazan, Russia, known as one of the country’s top teams and a regular competitor in European competitions such as the EuroCup and EuroLeague.
  • 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_69d6ab67950c8190be08450a06228c4b completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91ccadc3c81908fe68adc3fdcc851 completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60abfc8588190ab9300c6e5e59092 completed May 2, 2026, 2:31 p.m.
Created at: April 8, 2026, 9:52 p.m.