Triple

T3537352
Position Surface form Disambiguated ID Type / Status
Subject Princess Peach E74800 entity
Predicate ally P4662 FINISHED
Object Mario E31492 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: [Princess Peach, ally, Mario]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mario
Context triple: [Princess Peach, ally, Mario]
  • A. Mario
    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 chosen
    Mario is a fictional Italian plumber and the iconic protagonist of Nintendo's long-running Super Mario video game franchise.
  • C. 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.
  • D. Baby Mario
    Baby Mario is the infant version of Nintendo’s iconic hero Mario, appearing as a playable character in various Mario spin-off and Yoshi games.
  • E. Paper Mario
    Paper Mario is a role-playing video game series by Nintendo that features a distinctive paper-like art style and turn-based combat starring Mario in humorous, story-driven adventures.
  • 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_69ad85d274cc8190ab59c97298a1cfbf completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbcc928248190b851f8280d58cfcf completed March 8, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69b402dbd7d08190b7b220aa8c7caac6 completed March 13, 2026, 12:28 p.m.
Created at: March 8, 2026, 3:20 p.m.