Triple
T24559358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raga Bhairav |
E607609
|
entity |
| Predicate | aestheticMood |
P62080
|
FINISHED |
| Object | serious |
—
|
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: serious | Statement: [Raga Bhairav, aestheticMood, serious]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aestheticMood Context triple: [Raga Bhairav, aestheticMood, serious]
-
A.
associatedAesthetic
Indicates a relationship where one entity is linked to or characterized by a particular aesthetic style, quality, or visual/theme-based sensibility.
-
B.
featuresMood
chosen
Indicates that something includes, presents, or conveys a particular mood or emotional atmosphere.
-
C.
depictsMood
Indicates that one entity visually represents or conveys the emotional state or mood of another entity.
-
D.
artisticStyle
Indicates the artistic movement, style, or aesthetic approach that characterizes how something is created or visually expressed.
-
E.
lyricalMood
Indicates the prevailing emotional tone or atmosphere conveyed through lyrics or vocal expression in a piece of music.
- 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_69e2c4cae1b88190825e88d5ce8aa61e |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8f4af6481908576473adab9f6bf |
completed | April 30, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:27 a.m.