Triple
T3249071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fun and Fancy Free |
E68132
|
entity |
| Predicate | follows |
P134
|
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: [Fun and Fancy Free, follows, Make Mine Music]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Make Mine Music Context triple: [Fun and Fancy Free, follows, 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf3fc3c8819080ac95974581ca0e |
completed | March 8, 2026, 5:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28eb55734819093f470caacc3e29c |
completed | March 12, 2026, 10 a.m. |
Created at: March 8, 2026, 3:09 p.m.