Triple
T29101411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yamaha YMF276 |
E736647
|
entity |
| Predicate | audioSynthesisType |
P82797
|
FINISHED |
| Object | 2-operator FM synthesis |
—
|
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: 2-operator FM synthesis | Statement: [Yamaha YMF276, audioSynthesisType, 2-operator FM synthesis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audioSynthesisType Context triple: [Yamaha YMF276, audioSynthesisType, 2-operator FM synthesis]
-
A.
soundSynthesisType
chosen
Indicates the method or technique used to generate or construct a sound signal.
-
B.
speechType
Indicates the specific category or form of spoken or written communication that an utterance or speech act belongs to (e.g., question, statement, command).
-
C.
voiceTexture
Indicates the characteristic quality or timbre of a voice as perceived in sound.
-
D.
voiceActingType
Indicates the specific style or category of voice performance used in an audio-visual work or production.
-
E.
speakerType
Indicates the role or category of a participant in a communicative act (e.g., narrator, quoted speaker, system voice) within a given context.
- 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_69f077ec765c81909474c88bcc8bab43 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6645ba71c81908044ade6ab577018 |
completed | May 2, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f663362c008190a22afed262f1e426 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 11:12 a.m.