Triple
T13745581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harder, Better, Faster, Stronger |
E330200
|
entity |
| Predicate | hasVocalProcessing |
P110805
|
FINISHED |
| Object | vocoder |
—
|
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: vocoder | Statement: [Harder, Better, Faster, Stronger, hasVocalProcessing, vocoder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVocalProcessing Context triple: [Harder, Better, Faster, Stronger, hasVocalProcessing, vocoder]
-
A.
hasVocals
Indicates that the subject includes or features vocal elements, such as singing or spoken voice, rather than being purely instrumental or non-vocal.
-
B.
hasVocalForces
Indicates that an entity involves or employs vocal performers or vocal parts as a contributing force.
-
C.
hasVocalLanguageMix
Indicates that an entity’s vocal communication combines multiple languages or language varieties within its speech.
-
D.
usesVocalOverdubbing
Indicates that one entity applies vocal overdubbing to another entity, layering additional recorded vocals over an existing audio track.
-
E.
hasVoiceIn
Indicates that an entity participates by providing a voice role or vocal performance in another entity, such as a work, production, or recording.
- F. None of above. chosen
Provenance (4 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0211ba5481909fbd5b447e3d5a02 |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe950b148190ba0df8a749269ec6 |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59db0148190bcaf9646403ca64f |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 10:08 p.m.