Triple
T15950630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | If I Had No Loot |
E386806
|
entity |
| Predicate | usesVocalSamples |
P121092
|
FINISHED |
| Object | hip-hop–style vocal samples |
—
|
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: hip-hop–style vocal samples | Statement: [If I Had No Loot, usesVocalSamples, hip-hop–style vocal samples]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesVocalSamples Context triple: [If I Had No Loot, usesVocalSamples, hip-hop–style vocal samples]
-
A.
containsVocalSamplesFrom
Indicates that one audio work includes vocal samples that originate from another audio work.
-
B.
hasVocals
Indicates that the subject includes or features vocal elements, such as singing or spoken voice, rather than being purely instrumental or non-vocal.
-
C.
usesVocalInstrument
Indicates that an entity performs or produces sound using their voice as a musical instrument.
-
D.
usesVocalOverdubbing
Indicates that one entity applies vocal overdubbing to another entity, layering additional recorded vocals over an existing audio track.
-
E.
hasBackwardVocals
Indicates that the subject uses or contains backward (reversed) vocal audio in relation to the object.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d37cd88190ab50760f1783e20c |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:53 a.m.