Triple

T12733933
Position Surface form Disambiguated ID Type / Status
Subject Jason Kreis E304312 entity
Predicate awardReceived P11 FINISHED
Object MLS Golden Boot E181684 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: MLS Golden Boot | Statement: [Jason Kreis, awardReceived, MLS Golden Boot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MLS Golden Boot
Context triple: [Jason Kreis, awardReceived, MLS Golden Boot]
  • A. MLS Golden Boot chosen
    The MLS Golden Boot is Major League Soccer’s annual award given to the league’s top goal scorer in the regular season.
  • B. Golden Boot
    The Golden Boot is a football award given to the top goal scorer at major tournaments, including the FIFA Club World Cup.
  • C. Golden Boot Award
    The Golden Boot Award is an international rugby league honor presented annually to the player judged to be the best in the world.
  • D. Golden Boot Award
    The Golden Boot Award is an honor recognizing significant contributions to the Western genre in film and television, often awarded to actors, directors, and other industry figures.
  • E. FIFA World Cup Golden Boot
    The FIFA World Cup Golden Boot is the award given to the tournament's top goal scorer.
  • 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_69d7bdf1426c8190a4402e1c4cdec33a completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9646902408190b29268d864833b80 completed April 10, 2026, 8:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c8e2dbc81909c1c85ca699a2679 completed May 2, 2026, 10:37 p.m.
Created at: April 9, 2026, 5:26 p.m.