Triple

T10188959
Position Surface form Disambiguated ID Type / Status
Subject You Can Count on Me E237982 entity
Predicate producer P490 FINISHED
Object John Hart E76182 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: John Hart | Statement: [You Can Count on Me, producer, John Hart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Hart
Context triple: [You Can Count on Me, producer, John Hart]
  • A. John Hart chosen
    John Hart is a film producer best known for his work on literary adaptations and independent movies, including the 2002 adaptation of "Nicholas Nickleby."
  • B. John Hart
    John Hart is the son of former U.S. Senator and 1980s Democratic presidential contender Gary Hart.
  • C. Jeffrey Konvitz
    Jeffrey Konvitz is an American author and film producer best known for his 1974 horror novel "The Sentinel," which was adapted into a feature film.
  • D. John A. Griswold
    John A. Griswold was a 19th-century American industrialist, U.S. Congressman from New York, and prominent figure in Troy’s iron and steel industry.
  • E. James V. Hart
    James V. Hart is an American screenwriter and producer best known for adapting classic literary and fantasy works for film, including projects like "Bram Stoker's Dracula" and "Hook."
  • 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_69ca84de1b208190bf17bb305b002605 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cded7c3278819093312665b54d888c completed April 2, 2026, 4:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d317b734a4819085645caea8ba0481 completed April 6, 2026, 2:17 a.m.
Created at: March 30, 2026, 9:12 p.m.