Triple
T29088260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Brazileira |
E734180
|
entity |
| Predicate | hasPrimaryRegionOfMusicalOrigin |
P118703
|
FINISHED |
| Object | Brazil |
—
|
NE NERFINISHED |
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: Brazil | Statement: [A Brazileira, hasPrimaryRegionOfMusicalOrigin, Brazil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryRegionOfMusicalOrigin Context triple: [A Brazileira, hasPrimaryRegionOfMusicalOrigin, Brazil]
-
A.
hasPrimaryGenreRegion
chosen
Indicates that an entity’s main or dominant genre is associated with a particular geographic region.
-
B.
hasGenreOfOrigin
Indicates that an entity’s original or primary genre classification is the specified genre.
-
C.
laterCountryOfOrigin
Indicates that an entity’s country of origin changed, and this predicate specifies the country that became its origin at a later time than a previously associated country.
-
D.
hasRhythmOrigin
Indicates that one rhythm, style, or rhythmic pattern originates from, is derived from, or has its roots in another source.
-
E.
countryOfOriginForMusicCareer
Indicates the country where an artist’s professional music career was primarily started or established.
- 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_69f05b0c0f28819086eae6e84f2ae472 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69ff397e19a88190a945b826159f5290 |
completed | May 9, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69ff392400d0819088d30d08d4a774bd |
completed | May 9, 2026, 1:39 p.m. |
Created at: April 28, 2026, 11:02 a.m.