Triple
T24455817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Way Cool Jr. |
E616679
|
entity |
| Predicate | isBluesInfluenced |
P22766
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Way Cool Jr., isBluesInfluenced, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBluesInfluenced Context triple: [Way Cool Jr., isBluesInfluenced, true]
-
A.
isBluesy
Indicates that something possesses qualities or characteristics typical of blues music, such as its style, mood, or expressive feel.
-
B.
isBluesStandard
Indicates that a musical piece follows the conventional structure, harmony, and form commonly recognized as a blues standard.
-
C.
influencedInstrument
Indicates that one entity has affected, shaped, or altered a musical instrument or tool in some way, such as its design, use, style, or development.
-
D.
hasInfluentialRiff
Indicates that one musical riff has had a significant impact on or has strongly influenced another piece, style, or musician.
-
E.
hasGenreInfluenceOn
chosen
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
- 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_69e2d7ef9fe08190a0613908758b4e86 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f298c5b510819099a92da4c100ded1 |
completed | April 29, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:18 a.m.