Triple
T9853268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babla |
E239521
|
entity |
| Predicate | primaryRegionOfInfluence |
P9666
|
FINISHED |
| Object | Indo-Caribbean music scene |
—
|
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: Indo-Caribbean music scene | Statement: [Babla, primaryRegionOfInfluence, Indo-Caribbean music scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryRegionOfInfluence Context triple: [Babla, primaryRegionOfInfluence, Indo-Caribbean music scene]
-
A.
influencesRegion
Indicates that one entity has an effect on, shapes, or alters the conditions, characteristics, or behavior of a specified region.
-
B.
primaryRegionOfPopularity
chosen
Indicates the geographic region where something is most widely used, favored, or popular compared to other regions.
-
C.
hasRegionalInfluenceFrom
Indicates that one entity’s influence, impact, or authority in a region is derived from or shaped by another entity.
-
D.
impactRegion
Indicates the geographic or spatial area that is affected or influenced by a particular event, action, or phenomenon.
-
E.
primaryInfluence
Indicates that one entity serves as the main or most significant influencing factor on another entity’s state, behavior, or outcome.
- 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb376d32c819089381cf6ed83629d |
completed | April 2, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69cd03e57cac8190914bb5ae608a6e0e |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:34 p.m.