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README.md

@@ -175,7 +175,7 @@ This dataset is released under **CC-BY-4.0**. OHADA court decisions are public l
 ```python
 from datasets import load_dataset
 
-dataset = load_dataset("Maathis-com/ohada-ccja-corpus")
+dataset = load_dataset("YOUR_USERNAME/ohada-ccja-corpus")
 
 # Access splits
 train = dataset["train"]
@@ -189,7 +189,7 @@ print(train[0])
 from datasets import load_dataset
 from sklearn.metrics import classification_report
 
-dataset = load_dataset("Maathis-com/ohada-ccja-corpus")
+dataset = load_dataset("YOUR_USERNAME/ohada-ccja-corpus")
 
 # Use dispute_summary as input, legal_domain as label
 train_texts = dataset["train"]["dispute_summary"]
@@ -203,9 +203,9 @@ If you use this dataset in your research, please cite:
 ```bibtex
 @dataset{ohada_ccja_corpus_2026,
   title={OHADA-CCJA Court Decisions Corpus: A Dataset for African Legal NLP},
-  author={Foutse Yuehgoh, Priyanka N, Patrick NGUETCHOUESSI},
+  author={Foutse Yuehgoh},
   year={2026},
-  url={https://huggingface.co/datasets/Maathis-com/ohada-ccja-corpus},
+  url={https://huggingface.co/datasets/YOUR_USERNAME/ohada-ccja-corpus},
   note={Presented at Deep Learning Indaba 2026, Nigeria}
 }
 ```

dataset_info.json

@@ -12,8 +12,8 @@
     "test": 609,
     "validation": 609
   },
-  "date_range": "1970-2025",
-  "legal_domains": 18,
+  "date_range": "1997-2023",
+  "legal_domains": 16,
   "features": [
     "case_id",
     "case_number",

full_dataset.csv

@@ -1,3 +1,3 @@
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+oid sha256:56711149fefc4afcf3ab32c9742d9484389ec3d0dcb52d571c12b1220da0d237
+size 44212656

test.parquet

@@ -1,3 +1,3 @@
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+size 3135366

train.parquet

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+size 13884946

validation.parquet

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