Triple
T14660365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sorry (Justin Bieber song) |
E344219
|
entity |
| Predicate | hasDancehallInfluence |
P22766
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Sorry (Justin Bieber song), hasDancehallInfluence, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDancehallInfluence Context triple: [Sorry (Justin Bieber song), hasDancehallInfluence, yes]
-
A.
hasDanceInfluence
Indicates that one entity has contributed to shaping, inspiring, or affecting the dance style, technique, or choreography of another entity.
-
B.
hasGenreInfluenceOn
chosen
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
C.
hasDanceableRhythm
Indicates that something possesses a rhythm or beat suitable for dancing.
-
D.
hasDiasporaInfluenceOn
Indicates that a diaspora community exerts cultural, social, economic, or political influence on another entity, such as a country, region, or group.
-
E.
hasEthnicInfluence
Indicates that one entity has a cultural, traditional, or ethnic impact on, or contributes to shaping the ethnic character 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb51c84448190a1f5fa9ab8a1e2c4 |
completed | April 14, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69de6576f0208190aa94d995e797ac38 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:27 a.m.