Triple

T15938183
Position Surface form Disambiguated ID Type / Status
Subject Too Hot to Sleep E386491 entity
Predicate producer P490 FINISHED
Object Frank Filipetti E894597 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: Frank Filipetti | Statement: [Too Hot to Sleep, producer, Frank Filipetti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frank Filipetti
Context triple: [Too Hot to Sleep, producer, Frank Filipetti]
  • A. Frank Filipetti chosen
    Frank Filipetti is a Grammy-winning American record producer and audio engineer known for his work with major artists across pop, rock, and Broadway cast recordings.
  • B. Michael Fetterly
    Michael Fetterly is a voice actor known for portraying the character Uncle Fester in an adaptation of The Addams Family.
  • C. Frank Faylen
    Frank Faylen was an American character actor best known for his supporting roles in classic films like "It's a Wonderful Life" and "The Lost Weekend," as well as numerous television appearances.
  • D. Fred Nicolaus
    Fred Nicolaus is an American musician and songwriter best known as one half of the indie rock duo Department of Eagles.
  • E. Frank Leonetti
    Frank Leonetti is a relative of American cinematographer and film director John R. Leonetti, known for his work in the film industry.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156ac934c8190b6178eb66023252e completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3bfe72c819095f40a255bcd7ad5 completed May 9, 2026, 11:31 p.m.
Created at: April 10, 2026, 4:53 a.m.