Triple
T15415722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sensual Seduction |
E369221
|
entity |
| Predicate | vocalEffects |
P118708
|
FINISHED |
| Object | Auto-Tune |
—
|
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: Auto-Tune | Statement: [Sensual Seduction, vocalEffects, Auto-Tune]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vocalEffects Context triple: [Sensual Seduction, vocalEffects, Auto-Tune]
-
A.
voiceEffectsBy
Indicates that one entity applies or produces voice-related effects that modify or transform the voice of another entity.
-
B.
vocal
Indicates that an entity produces or is characterized by audible sounds, speech, or vocalizations.
-
C.
hasVocalForces
Indicates that an entity involves or employs vocal performers or vocal parts as a contributing force.
-
D.
vocalForces
Indicates a relationship where one entity uses vocal expression (such as speech, singing, or sound) to exert influence, pressure, or compulsion on another entity.
-
E.
vocalTraining
Indicates that one entity provides or engages in training aimed at improving another entity’s vocal or singing abilities.
- 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ea8a8a081909749db1b29d85fcc |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded27f45548190a6d2b1b85cb47444 |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57005608190886cd01f640dfedb |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 3:20 a.m.