Triple
T13737549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Streetlife |
E329989
|
entity |
| Predicate | hasMusicalInfluenceFrom |
P87217
|
FINISHED |
| Object | Wu-Tang Clan sound |
—
|
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: Wu-Tang Clan sound | Statement: [Streetlife, hasMusicalInfluenceFrom, Wu-Tang Clan sound]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMusicalInfluenceFrom Context triple: [Streetlife, hasMusicalInfluenceFrom, Wu-Tang Clan sound]
-
A.
influencesMusicOf
Indicates that one entity has an effect on, shapes, or contributes to the musical style, content, or development of another entity.
-
B.
influencedArtist
Indicates that one artist has had a significant impact on the style, work, or development of another artist.
-
C.
wereInfluencedBy
chosen
Indicates that one entity’s ideas, actions, or characteristics were shaped or affected by another entity.
-
D.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
E.
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.
- 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_69d80772315881908f980cae40d91664 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de0204d50c8190a5413cc9a1b26e14 |
completed | April 14, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69dbbe950b148190ba0df8a749269ec6 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:55 p.m.