Triple

T5166320
Position Surface form Disambiguated ID Type / Status
Subject The Golden Turkey Awards E116566 entity
Predicate author P4 FINISHED
Object Michael Medved
Michael Medved is an American film critic, radio host, and author known for his conservative commentary and popular books on movies and culture.
E500243 NE FINISHED

How this triple was built (4 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: Michael Medved | Statement: [The Golden Turkey Awards, author, Michael Medved]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Medved
Context triple: [The Golden Turkey Awards, author, Michael Medved]
  • A. John Batchelor
    John Batchelor is an Australian actor known for his work in film, television, and theatre.
  • B. Jason Hart
    Jason Hart is a former American professional basketball player who later became a college coach.
  • C. Mike Savage
    Mike Savage is a Canadian politician who has served as the mayor of Halifax, Nova Scotia.
  • D. Max Borenstein
    Max Borenstein is an American screenwriter and producer best known for his work on the modern Godzilla and MonsterVerse films.
  • E. Kevin Barrett
    Kevin Barrett is a former New Zealand rugby union player and Taranaki stalwart, best known as the father of All Blacks stars including Beauden Barrett.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Michael Medved
Triple: [The Golden Turkey Awards, author, Michael Medved]
Generated description
Michael Medved is an American film critic, radio host, and author known for his conservative commentary and popular books on movies and culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Michael Medved
Target entity description: Michael Medved is an American film critic, radio host, and author known for his conservative commentary and popular books on movies and culture.
  • A. John Batchelor
    John Batchelor is an Australian actor known for his work in film, television, and theatre.
  • B. Jason Hart
    Jason Hart is a former American professional basketball player who later became a college coach.
  • C. Mike Savage
    Mike Savage is a Canadian politician who has served as the mayor of Halifax, Nova Scotia.
  • D. Max Borenstein
    Max Borenstein is an American screenwriter and producer best known for his work on the modern Godzilla and MonsterVerse films.
  • E. Kevin Barrett
    Kevin Barrett is a former New Zealand rugby union player and Taranaki stalwart, best known as the father of All Blacks stars including Beauden Barrett.
  • F. None of above. chosen

Provenance (5 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_69bd445edb3881909b93b34d260717fc completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd792c5ea88190b6aa0e519c744155 completed March 20, 2026, 4:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed93b85188190927d448e09a46425 completed March 21, 2026, 5:45 p.m.
NEDg Description generation batch_69bedbd301088190908d050425c6cda7 completed March 21, 2026, 5:56 p.m.
NED2 Entity disambiguation (via description) batch_69bedc65fcdc8190bc99c0d049e4dd94 completed March 21, 2026, 5:59 p.m.
Created at: March 20, 2026, 1:44 p.m.