Triple

T10384908
Position Surface form Disambiguated ID Type / Status
Subject Sport Australia Hall of Fame E244735 entity
Predicate awardGiven P287 FINISHED
Object The Don Award E859039 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: The Don Award | Statement: [Sport Australia Hall of Fame, awardGiven, The Don Award]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Don Award
Context triple: [Sport Australia Hall of Fame, awardGiven, The Don Award]
  • A. The Don Award chosen
    The Don Award is a prestigious Australian sporting honor presented annually to the athlete or team whose performance and example most inspired the nation.
  • B. Biletnikoff Award
    The Biletnikoff Award is an annual college football honor presented to the nation’s most outstanding receiver at any position.
  • C. Les Cunningham Award
    The Les Cunningham Award is the American Hockey League’s annual honor given to its most valuable player during the regular season.
  • D. Reuben Award
    The Reuben Award is a prestigious annual honor presented by the National Cartoonists Society to recognize outstanding achievement in the field of cartooning.
  • E. Tony Jannus Award
    The Tony Jannus Award is a prestigious aviation honor recognizing outstanding contributions to the commercial airline industry.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9a35fb08190ab85b4a8f8dea511 completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fba398b88190ae3223218bf53ca7 completed April 9, 2026, 7:18 p.m.
Created at: April 6, 2026, 12:04 p.m.