Triple

T3597906
Position Surface form Disambiguated ID Type / Status
Subject Kamek E76184 entity
Predicate appearsIn P795 FINISHED
Object Mario franchise E74796 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 franchise | Statement: [Kamek, appearsIn, Mario franchise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mario franchise
Context triple: [Kamek, appearsIn, Mario franchise]
  • A. Mario
    Mario is a fictional Italian plumber and the iconic protagonist of Nintendo's long-running Super Mario video game franchise.
  • B. Mario
    Mario is an American R&B singer, songwriter, and occasional actor best known for his early-2000s hits like "Let Me Love You."
  • C. Yoshi series
    The Yoshi series is a platform game franchise by Nintendo that stars the dinosaur Yoshi in colorful, often puzzle-oriented adventures spun off from the Super Mario series.
  • D. Nintendo video games chosen
    Nintendo video games are a long-running and influential collection of video game titles created or published by Nintendo, known for iconic franchises like Super Mario, The Legend of Zelda, and Pokémon.
  • E. Mario & Luigi
    Mario & Luigi is a role-playing video game series by Nintendo that follows the comedic, cooperative adventures of Mario and his brother Luigi.
  • 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_69ad85d8042081908af94a04c410dec0 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc19c71608190a87c98214321214c completed March 8, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b43307cb548190824bb6704e339bff completed March 13, 2026, 3:53 p.m.
Created at: March 8, 2026, 3:22 p.m.