Triple

T4752807
Position Surface form Disambiguated ID Type / Status
Subject Ondrej Nepela Memorial E105516 entity
Predicate namedAfter P63 FINISHED
Object Ondrej Nepela E102755 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: Ondrej Nepela | Statement: [Ondrej Nepela Memorial, namedAfter, Ondrej Nepela]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ondrej Nepela
Context triple: [Ondrej Nepela Memorial, namedAfter, Ondrej Nepela]
  • A. Ondrej Nepela chosen
    Ondrej Nepela was a Slovak figure skater and 1972 Olympic champion, regarded as one of the most successful skaters of his era.
  • B. Scott Hamilton
    Scott Hamilton is an American figure skating champion and Olympic gold medalist who later became a prominent television commentator and public figure.
  • C. Pavel Kurochkin
    Pavel Kurochkin was a Soviet military commander and general who held key leadership roles in the Red Army during World War II.
  • D. Vladimir Yurzinov
    Vladimir Yurzinov is a prominent Russian ice hockey coach and former player, best known for his successful leadership of top Soviet and Russian clubs and contributions to the national team.
  • E. Emil Zátopek
    Emil Zátopek was a legendary Czech long-distance runner renowned for his multiple Olympic gold medals and pioneering, brutally intense training methods.
  • 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_69bd43f07fa48190954317d01600994a completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64e5fba88190b1f28d1b0eed3f8e completed March 20, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a5ddf088190892d31275adb39ba completed March 21, 2026, 6:27 a.m.
Created at: March 20, 2026, 1:20 p.m.