Triple

T27094629
Position Surface form Disambiguated ID Type / Status
Subject AMA Pro Motocross Championship rounds E686259 entity
Predicate pointsAwarded P161848 FINISHED
Object championship 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: championship points | Statement: [AMA Pro Motocross Championship rounds, pointsAwarded, championship points]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: pointsAwarded
Context triple: [AMA Pro Motocross Championship rounds, pointsAwarded, championship points]
  • A. pointsEarnedFrom
    Indicates the number of points that an entity has received as a result of another specified source, action, or event.
  • B. winnerPoints
    Indicates the number of points earned by the winning participant or entity in a competition or event.
  • C. positionAwarded
    Indicates that a specific position, role, or title has been formally granted to an entity (such as a person or organization).
  • D. penaltyPoints
    Indicates that a certain number of negative points or demerits are assigned to an entity as a consequence of a rule violation, error, or infraction.
  • E. pointsForWin
    Indicates the number of points awarded to an entity for achieving a win in a given context or competition.
  • F. None of above. chosen

Provenance (4 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_69ef1489f8b481908e24a1985982bd26 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f623ae732c8190b311ac72d7b6bda2 completed May 2, 2026, 4:17 p.m.
PD Predicate disambiguation batch_69f61b40f02081909bd9c3ea73249163 completed May 2, 2026, 3:41 p.m.
PDg Predicate description generation batch_69f61fa35ac48190890102c348ed81a0 completed May 2, 2026, 4 p.m.
Created at: April 27, 2026, 8:43 a.m.