Triple
T4415826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angolar |
E94969
|
entity |
| Predicate | isSpokenAlongside |
P25756
|
FINISHED |
| Object | Forro |
E94968
|
NE 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: Forro | Statement: [Angolar, isSpokenAlongside, Forro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Forro Context triple: [Angolar, isSpokenAlongside, Forro]
-
A.
Forro
chosen
Forro is a Portuguese-based creole language spoken primarily on the islands of São Tomé and Príncipe in the Gulf of Guinea.
-
B.
Batuque
Batuque is an Afro-Brazilian religious tradition that blends West African (especially Yoruba) spiritual practices with elements of Catholicism and Indigenous beliefs, centered on the worship of orixás through music, dance, and ritual.
-
C.
Rumba
Rumba is one of the spacecraft in the Cluster mission, a European Space Agency project studying Earth's magnetosphere in three dimensions.
-
D.
Afroswing
Afroswing is a UK-born music genre that fuses elements of Afrobeats, dancehall, hip hop, and R&B into a melodic, rhythm-driven sound.
-
E.
Macaxeira
Macaxeira is a neighborhood in the city of Recife, Brazil.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69b34539638c8190abfea3eb29425210 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35640269c8190a88fc6b59070561b |
completed | March 13, 2026, 12:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b613664c548190b5cd0c2667baecc7 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:29 p.m.