Triple

T15384859
Position Surface form Disambiguated ID Type / Status
Subject Blue Shell E367890 entity
Predicate universe P4832 FINISHED
Object Mario franchise E406903 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: [Blue Shell, universe, Mario franchise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mario franchise
Context triple: [Blue Shell, universe, Mario franchise]
  • A. Super Mario series chosen
    The Super Mario series is Nintendo’s flagship platform game franchise starring Mario in a wide variety of adventures across imaginative worlds.
  • B. 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.
  • C. Mario
    Mario is a fictional Italian plumber and the iconic protagonist of Nintendo's long-running Super Mario video game franchise.
  • D. Mario
    Mario is an American R&B singer, songwriter, and occasional actor best known for his early-2000s hits like "Let Me Love You."
  • E. Splash franchise
    The Splash franchise is a romantic fantasy-comedy film series centered around mermaids and their relationships with humans, originating from the 1984 movie "Splash."
  • 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_69d85a1551a08190ba2caea7cd51c639 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e7397188190bde42b897ab4b5b4 completed April 16, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff8757325c8190ad97f50368862ca5 completed May 9, 2026, 7:13 p.m.
Created at: April 10, 2026, 3:19 a.m.