Triple
T19967220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Yeletsky |
E479967
|
entity |
| Predicate | emotionalToneOfMusic |
P45521
|
FINISHED |
| Object | lyrical |
—
|
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: lyrical | Statement: [Prince Yeletsky, emotionalToneOfMusic, lyrical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionalToneOfMusic Context triple: [Prince Yeletsky, emotionalToneOfMusic, lyrical]
-
A.
lyricalMood
chosen
Indicates the prevailing emotional tone or atmosphere conveyed through lyrics or vocal expression in a piece of music.
-
B.
inTonality
Indicates that something (such as a musical element, passage, or piece) is expressed, structured, or interpreted within a specific musical key or tonal framework.
-
C.
hasEmotiveVocals
Indicates that the subject produces vocals characterized by strong or expressive emotion.
-
D.
emotionalDynamic
Indicates how emotions, moods, or affective states change, interact, or influence each other between entities over time.
-
E.
contributesToTone
Indicates that one entity plays a role in shaping, influencing, or determining the overall tone or mood of another entity.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bc5e41881908c1e8867820f1c0c |
completed | April 20, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69e537f7e4848190b431a69ec3f1b609 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.