Triple
T5019355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Carpenter films |
E112810
|
entity |
| Predicate | typicalMusicStyle |
P22764
|
FINISHED |
| Object | synthesizer-based score |
—
|
LITERAL 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: synthesizer-based score | Statement: [John Carpenter films, typicalMusicStyle, synthesizer-based score]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMusicStyle Context triple: [John Carpenter films, typicalMusicStyle, synthesizer-based score]
-
A.
styleOfMusic
Indicates the musical genre or stylistic category that characterizes a piece of music, artist, or performance.
-
B.
hasMusicalStyleCharacteristic
Indicates that something possesses or exhibits a particular musical style as a defining characteristic.
-
C.
includesMusicalStyle
chosen
Indicates that one entity encompasses, features, or incorporates a particular musical style as part of its content or character.
-
D.
isPopularMusic
Indicates that the subject is a type of music that enjoys widespread appeal or mainstream popularity among listeners.
-
E.
primaryInstrumentalStyle
Indicates the main instrumental style or genre most closely associated with an entity’s musical performance or work.
- 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7342c62881909acb35849da8761c |
completed | March 20, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69bd714ecfe08190b5830cfc1c74fa17 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.