Triple

T15470048
Position Surface form Disambiguated ID Type / Status
Subject Paper Mario: Sticker Star E372133 entity
Predicate notableChangeFromPrequels P13888 FINISHED
Object removal of traditional experience points LITERAL 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: removal of traditional experience points | Statement: [Paper Mario: Sticker Star, notableChangeFromPrequels, removal of traditional experience points]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: notableChangeFromPrequels
Context triple: [Paper Mario: Sticker Star, notableChangeFromPrequels, removal of traditional experience points]
  • A. notableDifferenceFromDisneyAdaptation
    Indicates that something differs in a significant way from how it is portrayed in a Disney adaptation.
  • B. notableChange chosen
    Indicates a significant alteration or shift in the state, condition, or characteristics of an entity or relationship.
  • C. isPrequelTo
    Indicates that one work or event occurs earlier in time and narratively sets up or leads into another work or event.
  • D. prequelOrSequelTo
    Indicates that one work in a narrative series occurs earlier or later in the storyline or release order relative to another work, as its prequel or sequel.
  • E. protagonistAgeRelativeToPrequel
    Indicates how the protagonist’s age in the current work compares to their age in a preceding prequel story.
  • F. None of above.

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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f6b49788190b270fdfe92646842 completed April 16, 2026, 1:46 a.m.
PD Predicate disambiguation batch_69ded284bd008190b31c53b4f1cebadd completed April 14, 2026, 11:49 p.m.
Created at: April 10, 2026, 3:33 a.m.