Triple

T12582126
Position Surface form Disambiguated ID Type / Status
Subject Clive Charles E300363 entity
Predicate notableStudent P4838 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: [Clive Charles, notableStudent, Kasey Keller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kasey Keller
Context triple: [Clive Charles, notableStudent, 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 Anderson
    Casey Anderson is an American naturalist, wildlife expert, and television host best known for his work with grizzly bears and nature documentaries.
  • D. 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.
  • E. 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."
  • 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_69d7bde87b648190bcd0266e9efde098 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954b97a508190b6c901c506441dd0 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6559ba5108190b85be540a405eec8 completed May 2, 2026, 7:50 p.m.
Created at: April 9, 2026, 5:03 p.m.