Triple
T25700990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Big Bus (1976 film score) |
E644457
|
entity |
| Predicate | musicForWork |
P69477
|
FINISHED |
| Object | The Big Bus (1976 film) |
—
|
NE NERFINISHED |
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: The Big Bus (1976 film) | Statement: [The Big Bus (1976 film score), musicForWork, The Big Bus (1976 film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musicForWork Context triple: [The Big Bus (1976 film score), musicForWork, The Big Bus (1976 film)]
-
A.
songFromWork
Indicates that a song originates from, is part of, or is derived from a particular larger work (such as an album, film, show, or other production).
-
B.
musicUsed
chosen
Indicates that one entity makes use of or incorporates another entity as music, such as in a performance, production, or media context.
-
C.
musicMood
Indicates the emotional tone or atmosphere conveyed by a piece of music or musical performance.
-
D.
musicalWork
Indicates a relationship where an entity is identified as a musical composition or piece associated with another entity (such as a creator, performance, or recording).
-
E.
musicMotif
Indicates a recurring musical idea, theme, or pattern that appears multiple times within a composition or across related works.
- F. None of above.
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_69e77e82c9bc8190893090b2f6c64f1d |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f606c79ad081908369605f72e65ca6 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 21, 2026, 8:45 p.m.