Triple

T8096100
Position Surface form Disambiguated ID Type / Status
Subject Niklas Bäckström E188989 entity
Predicate team P3756 FINISHED
Object Oulun Kärpät E332001 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: Oulun Kärpät | Statement: [Niklas Bäckström, team, Oulun Kärpät]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oulun Kärpät
Context triple: [Niklas Bäckström, team, Oulun Kärpät]
  • A. Kärpät Oulu chosen
    Kärpät Oulu is a prominent Finnish professional ice hockey club from Oulu, known as one of the most successful teams in the Liiga.
  • B. Jokerit
    Jokerit is a professional ice hockey club from Helsinki, Finland, known as one of the country’s most successful and popular teams.
  • C. 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.
  • D. Ilves
    Ilves is a prominent Finnish sports club from Tampere best known for its ice hockey team competing in the country’s top professional league.
  • E. FC Honka
    FC Honka is a Finnish professional football club based in Espoo that competes in the country’s top-tier league.
  • 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_69ca82b886d88190a9cba0d5a4a27521 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4291f1d4819098985ac2b20b6c75 completed March 31, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc6414ca048190ac0e644b2c399bfb completed April 1, 2026, 12:17 a.m.
Created at: March 30, 2026, 5:30 p.m.