Triple

T14085300
Position Surface form Disambiguated ID Type / Status
Subject Daniel Sedin E338977 entity
Predicate memberOfSportsTeam P330 FINISHED
Object MODO Hockey E176287 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: MODO Hockey | Statement: [Daniel Sedin, memberOfSportsTeam, MODO Hockey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MODO Hockey
Context triple: [Daniel Sedin, memberOfSportsTeam, MODO Hockey]
  • A. Modo Hockey chosen
    Modo Hockey is a professional Swedish ice hockey club from Örnsköldsvik, known for its strong youth development and producing numerous NHL players.
  • B. Hockeyettan
    Hockeyettan is a Swedish ice hockey league that serves as a lower-tier division beneath the country’s top professional levels, featuring semi-professional and amateur clubs competing regionally.
  • C. Pro Hockey Life
    Pro Hockey Life is a Canadian retail chain specializing in hockey equipment, apparel, and accessories for players and fans.
  • D. NHL-2NA
    NHL-2NA is the internal codename used by Nokia for the Nokia 7650 mobile phone model.
  • E. Mestis
    Mestis is the second-highest level of professional ice hockey in Finland, sitting just below the top-tier Liiga.
  • 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_69d81c687b0c819087fd9ed4198403f8 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5edff1b881909ea56dc2429ef2dd completed April 14, 2026, 3:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdefe88b481908b3dca1f019e7809 completed May 7, 2026, 6:50 p.m.
Created at: April 9, 2026, 10:21 p.m.