Triple

T3240913
Position Surface form Disambiguated ID Type / Status
Subject Make Mine Music E67963 entity
Predicate title P38 FINISHED
Object Make Mine Music E67963 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: Make Mine Music | Statement: [Make Mine Music, title, Make Mine Music]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Make Mine Music
Context triple: [Make Mine Music, title, Make Mine Music]
  • A. Make Mine Music chosen
    Make Mine Music is a 1946 Walt Disney animated musical anthology film composed of ten segments set to popular and classical music.
  • B. Garland Waltz
    Garland Waltz is a famous waltz sequence from Tchaikovsky’s ballet "The Sleeping Beauty," often performed as a standalone concert piece.
  • C. Sweet Music Man
    "Sweet Music Man" is a country ballad written and originally recorded by Kenny Rogers, known for its reflective lyrics about the struggles of a fading music star.
  • D. With a Smile and a Song
    "With a Smile and a Song" is a cheerful, optimistic musical number sung by Snow White in Disney’s classic animated film Snow White and the Seven Dwarfs.
  • E. The Girl from Frisco
    The Girl from Frisco is a silent-era American film produced by the Vitagraph Company of America.
  • 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_69ad858d27348190abb61c280b4c86a9 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaef6430081909084589f6eea5c7e completed March 8, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b27754492c819099bab9a2a3344561 completed March 12, 2026, 8:20 a.m.
Created at: March 8, 2026, 3:08 p.m.