Triple

T5228726
Position Surface form Disambiguated ID Type / Status
Subject Roots E118055 entity
Predicate composer P1361 FINISHED
Object Gerald Fried E488540 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: Gerald Fried | Statement: [Roots, composer, Gerald Fried]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gerald Fried
Context triple: [Roots, composer, Gerald Fried]
  • A. Gerald Fried chosen
    Gerald Fried was an American composer best known for his film and television scores, including work on early Stanley Kubrick films and the original Star Trek series.
  • B. Leonard Rosenman
    Leonard Rosenman was an American composer best known for his innovative, modernist film and television scores in the 1950s and beyond.
  • C. Menahem Pressler
    Menahem Pressler was a renowned German-born American pianist and long-time founding member of the Beaux Arts Trio, celebrated for his chamber music and teaching.
  • D. Charles Fleischer
    Charles Fleischer is an American actor and comedian best known as the voice of Roger Rabbit and several other characters in the film "Who Framed Roger Rabbit."
  • E. Kenneth Sawyer Goodman
    Kenneth Sawyer Goodman was an American playwright and theatrical figure whose legacy inspired the founding of Chicago’s Goodman Theatre.
  • 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_69bd4466fb8c819083b806a79414d7e4 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7adee36881909b034b8735db9d67 completed March 20, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef80ca924819095bcc729feb0e464 completed March 21, 2026, 7:57 p.m.
Created at: March 20, 2026, 1:48 p.m.