Triple
T2220145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drunk in Love |
E48120
|
entity |
| Predicate | usesVocalStyle |
P29850
|
FINISHED |
| Object | melismatic singing |
—
|
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: melismatic singing | Statement: [Drunk in Love, usesVocalStyle, melismatic singing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesVocalStyle Context triple: [Drunk in Love, usesVocalStyle, melismatic singing]
-
A.
vocalizationMethod
Indicates the manner or technique by which an entity produces a sound or vocal expression.
-
B.
vocalizationCharacteristic
chosen
Indicates how an entity’s vocal sounds are characterized, such as their quality, style, or distinctive acoustic features.
-
C.
hasVocals
Indicates that the subject includes or features vocal elements, such as singing or spoken voice, rather than being purely instrumental or non-vocal.
-
D.
vocalizationUsage
Indicates how a particular vocalization is used or applied within a communicative or behavioral context.
-
E.
hasLyricalStyle
Indicates that one entity possesses or is characterized by a particular lyrical style in relation to another entity or 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc01386588190a9507f2969a201ca |
completed | March 7, 2026, 6:05 a.m. |
| PD | Predicate disambiguation | batch_69abbdac31d8819092d17815e11921e9 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.