Triple

T27571752
Position Surface form Disambiguated ID Type / Status
Subject MLS Scoring Champion Award E696053 entity
Predicate usedScoringMetric P48244 FINISHED
Object points instead of goals only 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: points instead of goals only | Statement: [MLS Scoring Champion Award, usedScoringMetric, points instead of goals only]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usedScoringMetric
Context triple: [MLS Scoring Champion Award, usedScoringMetric, points instead of goals only]
  • A. scoreUsedFor
    Indicates that a particular score or rating is used for a specific purpose, decision, or downstream process.
  • B. selectionMetric
    Indicates the criterion or measure used to evaluate and choose among alternative options or candidates.
  • C. usesCompositeScore
    Indicates that an entity bases its evaluation, decision, or outcome on a combined score derived from multiple underlying metrics or factors.
  • D. scoring
    Indicates the act of achieving points or a measurable result, typically by successfully completing an action that contributes to a score or outcome.
  • E. scoringType chosen
    Indicates the method or criteria by which performance, outcomes, or results are evaluated and assigned a score in a given context.
  • 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_69ef53891af88190a193c5e2a1dac9b1 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f6359e3d3c81909814e2f0a7fb0ea9 completed May 2, 2026, 5:34 p.m.
PD Predicate disambiguation batch_69f631871c888190bf29466fe4254e51 completed May 2, 2026, 5:16 p.m.
Created at: April 27, 2026, 1:43 p.m.