Triple

T13657207
Position Surface form Disambiguated ID Type / Status
Subject Kerner E326891 entity
Predicate hasNotableBearer P458 FINISHED
Object Jordan Kerner E359695 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: Jordan Kerner | Statement: [Kerner, hasNotableBearer, Jordan Kerner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jordan Kerner
Context triple: [Kerner, hasNotableBearer, Jordan Kerner]
  • A. Jordan Kerner chosen
    Jordan Kerner is an American film and television producer known for projects such as "Less Than Zero" and the live-action "The Smurfs" films.
  • B. Alex Kintner
    Alex Kintner is a young boy whose fatal shark attack at Amity Island becomes a pivotal and haunting event in the film "Jaws."
  • C. Jason Kehler
    Jason Kehler is a sports administrator who serves as the athletic director for the Dolphins athletic program.
  • D. Taylor Kornieck
    Taylor Kornieck is an American professional soccer midfielder known for her height, aerial ability, and playmaking, who has played in the National Women's Soccer League and for the U.S. women's national team.
  • E. Alex Kerner
    Alex Kerner is the idealistic young protagonist of the German film "Good Bye, Lenin!", who stages an elaborate ruse to protect his fragile mother from learning about the fall of East Germany.
  • 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_69d8076d8270819092afc2f0e9c359a8 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc61d56e4819084ae3c16ecdf4a05 completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7a83eddac81909376c36452bfa38b completed May 3, 2026, 7:55 p.m.
Created at: April 9, 2026, 9:52 p.m.