Triple

T3166558
Position Surface form Disambiguated ID Type / Status
Subject Kari Lehtonen E66224 entity
Predicate juniorTeam P8948 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: [Kari Lehtonen, juniorTeam, Jokerit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jokerit
Context triple: [Kari Lehtonen, juniorTeam, 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. Kärpät Oulu
    Kärpät Oulu is a prominent Finnish professional ice hockey club from Oulu, known as one of the most successful teams in the Liiga.
  • D. FC Honka
    FC Honka is a Finnish professional football club based in Espoo that competes in the country’s top-tier league.
  • E. 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.
  • 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_69ad8585d7988190af37365331093ccd completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada643e3e481908f4526d66e36e150 completed March 8, 2026, 4:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b276f529008190bc22ca454bd5d76b completed March 12, 2026, 8:19 a.m.
Created at: March 8, 2026, 3:06 p.m.