README.md

---
language:
- bm
- fr
task_categories:
- text-generation
size_categories:
- n<1K
tags:
- bambara
- text-normalization
- argilla
---

# text-normalization-benchmark

The raw [Argilla](https://github.com/argilla-io/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

```python
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>`.