Triple

T9775009
Position Surface form Disambiguated ID Type / Status
Subject Top 14 E237223 entity
Predicate bonusPointSystem P64949 FINISHED
Object offensive and defensive bonus 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: offensive and defensive bonus points | Statement: [Top 14, bonusPointSystem, offensive and defensive bonus points]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: bonusPointSystem
Context triple: [Top 14, bonusPointSystem, offensive and defensive bonus points]
  • A. awardSystem
    Indicates a relationship where an entity establishes or uses a structured scheme for granting awards, honors, or recognitions to others.
  • B. winnerPoints
    Indicates the number of points earned by the winning participant or entity in a competition or event.
  • C. hasBadgeSystem
    Indicates that an entity includes or supports a badge-based system for recognizing or tracking achievements, statuses, or milestones.
  • D. usesPointsSystem chosen
    Indicates that an entity operates or functions based on a structured points-based system for evaluation, rewards, or progression.
  • E. hasExerciseRewardSystem
    Indicates that an entity implements or is associated with a system that provides rewards or incentives for performing exercise or physical activity.
  • 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_69ca84d975a08190aab25b02a89bdab3 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda13148288190bcbb3b4a066d9fc1 completed April 1, 2026, 10:50 p.m.
PD Predicate disambiguation batch_69cd03d3b68c81909e570401a891b9f2 completed April 1, 2026, 11:38 a.m.
Created at: March 30, 2026, 8:26 p.m.