Datasets:
language:
- bm
- fr
task_categories:
- text-generation
size_categories:
- n<1K
tags:
- bambara
- text-normalization
- argilla
text-normalization-benchmark
The raw Argilla 2.8.0 export of a Bambara
(Bamanankan) text-normalization project: 160 records from four in-house corpora, each with
the annotator's standard-orthography rewrite. 96 carry a submitted response; 64 were
discarded. For a ready-to-score evaluation set, use
djelia/bm-text-normalization-benchmark, the cleaned export of the 96 finished annotations.
The repo is gated: request access on the Hub and run hf auth login.
Load
from datasets import load_dataset
ds = load_dataset("djelia/text-normalization-benchmark", split="train") # 160 rows
gold = ds.filter(lambda r: r["normalized_text.responses.status"][0] == "submitted")
pairs = [(r["source_text"], r["normalized_text.responses"][0]) for r in gold] # 96
The .argilla/ folder carries the schema, so the project reopens with
rg.Dataset.from_hub(...).
Fields
| Column | Description |
|---|---|
source_text |
The raw Bambara sentence to normalize |
normalized_text.responses |
List with the annotator's normalized text |
normalized_text.responses.status |
submitted (96) or discarded (64) |
source |
In-house corpus: bambara-asr-v2 50, Denube-final 50, transcription.txt 40, kunkado 20 |
status |
completed (96) or pending (64) |
Plus source_index, record identifiers, timestamps, the annotator UUID, and
normalized_text.suggestion — a UI pre-fill equal to source_text in every row.
Notes
Filter on the response status before treating anything as gold: a discarded response still
carries a value, in 62 of the 64 cases a copy of source_text.
33 of the submitted targets end in a trailing newline that no source_text contains; strip it
before any string-match metric.
Some rows carry transcription markers such as <INCOMPRÉHENSIBLE>.