Triple

T2327892
Position Surface form Disambiguated ID Type / Status
Subject Vladimir Yurzinov E48331 entity
Predicate coachedTeam P2169 FINISHED
Object Jokerit E66429 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: Jokerit | Statement: [Vladimir Yurzinov, coachedTeam, Jokerit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jokerit
Context triple: [Vladimir Yurzinov, coachedTeam, Jokerit]
  • A. Jokerit chosen
    Jokerit is a professional ice hockey club from Helsinki, Finland, known as one of the country’s most successful and popular teams.
  • B. HIFK Helsinki
    HIFK Helsinki is a prominent professional ice hockey club from Helsinki, Finland, known as one of the country’s most successful and traditional teams in the Liiga.
  • C. Brynas IF
    Brynäs IF is a professional Swedish ice hockey club based in Gävle, historically one of the country's most successful teams and a notable developer of NHL talent.
  • D. Frölunda HC
    Frölunda HC is a professional ice hockey club from Gothenburg, Sweden, competing in the top-tier Swedish Hockey League and known for its strong fan base and successful history.
  • E. Leksand
    Leksand is a small Swedish town in Dalarna County known for its traditional midsummer celebrations, picturesque lakeside setting, and strong ice hockey culture.
  • 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_69a88aa308a88190b0b86c011fda7fce completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc64c7f1881909b0d847f7782e803 completed March 7, 2026, 6:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae897243c48190a18b0e02ad664ead completed March 9, 2026, 8:48 a.m.
Created at: March 4, 2026, 7:50 p.m.