Triple

T3885415
Position Surface form Disambiguated ID Type / Status
Subject Press Play E92927 entity
Predicate hasGuestArtist P10644 FINISHED
Object Mario E95100 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 | Statement: [Press Play, hasGuestArtist, Mario]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mario
Context triple: [Press Play, hasGuestArtist, Mario]
  • A. Mario chosen
    Mario is an American R&B singer, songwriter, and occasional actor best known for his early-2000s hits like "Let Me Love You."
  • B. Mario
    Mario is a fictional Italian plumber and the iconic protagonist of Nintendo's long-running Super Mario video game franchise.
  • C. Mario vs. Donkey Kong series
    The Mario vs. Donkey Kong series is a puzzle-platform video game franchise in which Mario navigates intricate, toy-themed levels to outwit Donkey Kong and solve object-based challenges.
  • D. 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.
  • E. Super Mario series
    The Super Mario series is Nintendo’s flagship platform game franchise starring Mario in a wide variety of adventures across imaginative worlds.
  • 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_69aed9697de0819087c2559295ff3d12 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeec92cc548190b88b899299e5ccdc completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589b716648190aeaead138203cbf9 completed March 14, 2026, 4:15 p.m.
Created at: March 9, 2026, 3:20 p.m.