Triple

T11734966
Position Surface form Disambiguated ID Type / Status
Subject MLS Goalkeeper of the Year Award E279001 entity
Predicate hasRecipient P108 FINISHED
Object Kasey Keller E869225 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: Kasey Keller | Statement: [MLS Goalkeeper of the Year Award, hasRecipient, Kasey Keller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kasey Keller
Context triple: [MLS Goalkeeper of the Year Award, hasRecipient, Kasey Keller]
  • A. Kasey Keller chosen
    Kasey Keller is a former American goalkeeper known for his long professional career in Europe and Major League Soccer, as well as his key role with the United States national team in multiple World Cups.
  • B. Jason Keller
    Jason Keller is an American screenwriter best known for co-writing the racing drama film "Ford v Ferrari."
  • C. Casey Johnson
    Casey Johnson was an American socialite and heiress to the Johnson & Johnson fortune who gained media attention for her high-profile lifestyle and untimely death.
  • D. Casey Siemaszko
    Casey Siemaszko is an American actor best known for his roles in films such as "Back to the Future," "Stand by Me," and "Young Guns."
  • E. Trent Baalke
    Trent Baalke is an American football executive best known for his tenure as an NFL general manager, including leading front offices for multiple franchises.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4edced48190b7a59dd45921828e completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f0199f595081908c10ecd7dd3900e7 completed April 28, 2026, 2:21 a.m.
Created at: April 8, 2026, 9:41 p.m.