Triple

T15412868
Position Surface form Disambiguated ID Type / Status
Subject Diddy Kong E368636 entity
Predicate appearsInSeries P26455 FINISHED
Object Mario Tennis E167605 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: Mario Tennis | Statement: [Diddy Kong, appearsInSeries, Mario Tennis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mario Tennis
Context triple: [Diddy Kong, appearsInSeries, Mario Tennis]
  • A. Mario Tennis chosen
    Mario Tennis is a sports video game series by Nintendo that features Mario and other characters from the Mario franchise competing in arcade-style tennis matches.
  • B. Sony Open Tennis
    Sony Open Tennis was the former name of the prestigious annual professional tennis tournament held in Miami, Florida, that attracts top ATP and WTA players.
  • C. Virtua Tennis
    Virtua Tennis is a popular arcade-style tennis video game series known for its fast-paced gameplay and accessible controls.
  • D. Mario Golf
    Mario Golf is a sports video game series that combines golf gameplay with characters and elements from Nintendo’s Mario franchise.
  • E. Mario Superstar Baseball
    Mario Superstar Baseball is a GameCube sports video game that features characters from the Mario franchise competing in arcade-style baseball matches.
  • 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03ea600b48190a3dbca1a68a2a1cd completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f2754648190bfd0bd15f20b40d2 completed May 9, 2026, 4:21 p.m.
Created at: April 10, 2026, 3:20 a.m.