Triple

T6692500
Position Surface form Disambiguated ID Type / Status
Subject Dynamo Minsk E152660 entity
Predicate shortName P43 FINISHED
Object Dinamo Minsk E152660 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: Dinamo Minsk | Statement: [Dynamo Minsk, shortName, Dinamo Minsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dinamo Minsk
Context triple: [Dynamo Minsk, shortName, Dinamo Minsk]
  • A. Dynamo Minsk chosen
    Dynamo Minsk is a professional sports club from Minsk, Belarus, best known for its football team competing in the country’s top league and European competitions.
  • B. Dinamo Riga
    Dinamo Riga is a professional ice hockey club based in Riga, Latvia, known for competing in top European and international leagues.
  • C. Dynamo Moscow
    Dynamo Moscow is a prominent Russian professional ice hockey club based in Moscow, historically known for developing elite players such as Alex Ovechkin.
  • D. Dinamo
    Dinamo is a Romanian professional football club based in Bucharest, known for its rich history and passionate fan base.
  • E. Dinamo
    Dinamo is a Moscow Metro station named after the nearby Dynamo sports complex and stadium, serving passengers on the Zamoskvoretskaya Line.
  • 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_69c6880687b08190805278b504d1c92c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6b193a8c08190a99152a8eca018e6 completed March 27, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f7b70ef88190b605c3c70a941cdb completed March 27, 2026, 9:33 p.m.
Created at: March 27, 2026, 2:05 p.m.