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| license: cc-by-4.0 |
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| |
| # Eng-PidginEdu Dataset |
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| ## Overview |
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| Eng-PidginEdu is an English–Nigerian Pidgin parallel corpus developed to support machine translation, multilingual NLP, and educational accessibility research for low-resource African languages. |
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| The dataset contains **26,232 parallel sentence pairs** collected across **8 Nigerian secondary school subjects**, comprising approximately **1.09 million total tokens** with high-quality sentence-level alignment and human-validated translations. |
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| Nigerian Pidgin serves as a major lingua franca spoken across Nigeria and West Africa. This dataset was created to improve access to educational technologies and language resources for Pidgin-speaking communities. |
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|
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| # Dataset Composition |
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| ## Statistics |
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|
| | Metric | Value | |
| |---|---| |
| | Total Sentence Pairs | 26,232 | |
| | English Tokens | 555,398 | |
| | Pidgin Tokens | 533,657 | |
| | Avg English Sentence Length | 21.17 tokens | |
| | Avg Pidgin Sentence Length | 20.34 tokens | |
| | English TTR | 0.1032 | |
| | Pidgin TTR | 0.0883 | |
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|
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| ## Dataset Splits |
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|
| | Split | Size | |
| |---|---:| |
| | Train | 20,985 | |
| | Validation (Dev) | 2,623 | |
| | Test | 2,624 | |
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| The dataset was randomly shuffled using a fixed seed (`42`) to ensure reproducibility. |
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|
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| # Languages |
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| | Role | Language | Code | |
| |---|---|---| |
| | Source | English | `en` | |
| | Target | Nigerian Pidgin | `pcm` | |
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|
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| # Data Collection Process |
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| The dataset was compiled from publicly accessible Nigerian secondary school educational materials and curriculum-aligned learning resources. |
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| The data preparation pipeline included: |
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| 1. Document extraction using: |
| - `PyPDF2` |
| - `python-docx` |
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| 2. Sentence segmentation using: |
| - NLTK Punkt tokenizer |
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| 3. Text normalization and cleaning using: |
| - spaCy |
| - textacy |
| - regular-expression filtering |
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| 4. Translation generation using: |
| - `Davlan/mt5-small-en-pcm` |
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| 5. Human validation and correction by native Nigerian Pidgin speakers |
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| 6. Alignment verification and post-processing |
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| --- |
|
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| # Key Features |
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| - Large-scale English–Pidgin educational parallel corpus |
| - Coverage across multiple academic subjects |
| - Human-validated translations |
| - Natural Nigerian Pidgin expressions and code-switching |
| - Suitable for low-resource machine translation research |
| - Reproducible train/dev/test splits |
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|
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| # Intended Use |
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| This dataset is intended for: |
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| - Machine Translation (MT) |
| - Low-resource NLP research |
| - Educational AI systems |
| - Cross-lingual learning applications |
| - Multilingual language modeling |
| - Evaluation of African language translation systems |
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| --- |
|
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| # Limitations |
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| - Educational domain only |
| - Uneven subject distribution |
| - Contains orthographic variation in Nigerian Pidgin |
| - Includes informal and code-switched language patterns |
| - Does not represent all regional varieties of Nigerian Pidgin |
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|
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| # Bias and Ethical Considerations |
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| The dataset reflects naturally occurring educational language and may contain: |
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| - Curriculum-specific biases |
| - Subject imbalance |
| - Linguistic variation associated with Nigerian Pidgin usage |
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| No personally identifiable or sensitive information is included. |
| --- |
|
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| # Glossary and Terminology Resource |
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| In addition to the parallel sentence corpus, Eng-PidginEdu includes a bilingual educational glossary designed to improve terminology consistency and domain adaptation for machine translation systems. |
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| ## Glossary Statistics |
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| | Metric | Value | |
| |---|---:| |
| | Total Glossary Entries | 13,634 | |
| | Source Language | English | |
| | Target Language | Nigerian Pidgin | |
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|
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| ## Glossary Structure |
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| Each glossary entry contains: |
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| | Field | Description | |
| |---|---| |
| | `Technical_terms` | Educational or domain-specific English terminology | |
| | `Literal meaning` | Standard English explanation or definition | |
| | `pidgin meaning` | Nigerian Pidgin translation or interpretation | |
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| --- |
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| ## Example Entries |
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| | Technical Term | Literal Meaning | Pidgin Meaning | |
| |---|---|---| |
| | abandoned | Having been deserted or left | Leave am / throw away | |
| | abandonment | The act of giving something up | Di act of giving something up | |
| | abbreviated | Shortened form of something | Abbreviated na short form | |
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| --- |
|
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| ## Purpose of the Glossary |
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| The glossary was developed to: |
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| - Improve translation consistency across subjects |
| - Support educational terminology alignment |
| - Reduce mistranslation of technical concepts |
| - Assist low-resource terminology grounding |
| - Improve domain adaptation for MT systems |
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| The glossary was also used during post-processing and human validation to maintain consistency in subject-specific translations across Computer Science, Government, Biology, Business Studies, and related domains. |
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| --- |
|
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| ## Intended Use of the Glossary |
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| The glossary can be used for: |
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| - Terminology-aware machine translation |
| - Lexicon-constrained decoding |
| - Educational chatbot systems |
| - Bilingual terminology extraction |
| - Low-resource lexicon research |
| - Prompt engineering for LLM translation systems |
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| --- |
|
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| ## Notes |
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| - Some entries include naturally occurring Nigerian Pidgin paraphrases rather than strict literal translations. |
| - Orthographic variation may occur due to non-standardized spelling conventions in Nigerian Pidgin. |
| - Certain educational concepts may have multiple valid Pidgin renderings depending on context. |
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| --- |
|
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| # Glossary-Augmented Dataset (Eng-PidginEdu v2) |
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| `Eng-PidginEdu_glossary_augmented.csv`, also included in this repository, |
| is the parallel corpus above with the glossary merged directly into the |
| Pidgin translations: matched academic terms get their Pidgin meaning |
| inserted inline, in brackets, immediately after the term. |
|
|
| ``` |
| en: The ability for educators and students to adopt the |
| materials for free. |
| pcm: Teachers and students fit get the materials for free. |
| pcm_augmented: Teachers and students fit get the materials (tins wey |
| dem use for teaching) for free. |
| ``` |
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| This glossary-augmented file -- not the plain parallel corpus -- is the |
| actual training target used to fine-tune all 14 models in the |
| [Eng-PidginEdu benchmark](https://github.com/shashacode/Eng-PidginEdu-Benchmark), |
| and is the source of this project's novel glossary-accuracy evaluation |
| metric. |
|
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| ## Columns |
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| In addition to `en`, `pcm`, and `Subject` above: |
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| | Column | Description | |
| |---|---| |
| | `pcm_augmented` | The Pidgin translation with inline glosses inserted | |
| | `glossed_terms` | Semicolon-separated list of which terms were glossed in this row | |
| | `n_glosses` | Number of glosses inserted in this row | |
|
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| ## Augmentation statistics |
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| | Metric | Value | |
| |---|---:| |
| | Rows with at least one gloss | 16,114 / 26,232 (61.4%) | |
| | Total glosses inserted | 28,243 | |
| | Distinct terms glossed | 2,473 | |
|
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| ## Reproducing it |
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| The exact preprocessing script that produces this file from the raw |
| corpus and the standalone glossary table above is `glossary_augment.py`, |
| published in the |
| [benchmark's GitHub repository](https://github.com/shashacode/Eng-PidginEdu-Benchmark) -- |
| verified to reproduce this file exactly, byte-for-byte, across all |
| 26,232 rows. |
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| --- |
|
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| # Licensing |
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| This dataset is released under the **CC-BY-4.0 License**. |
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| --- |
|
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| # Citation |
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| If you use this dataset, please cite: |
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|
| ```bibtex |
| @dataset{eng_pidginedu_2026, |
| author = {Oladipupo, F., |
| Flora Oladipupo, Felix Akintola, Aleem Aduragbemi, Emmanuel Macaulay, Olisaemeka Nwosu, Adeniran Treasure, Michael Kanu, Jennifer Ochonogor, Victor Jayeoba, Zion O. Oluwasegun, Gift Warieta, Joy Adebiyi, Consolation U. Obazee}, |
| title = {Eng-PidginEdu: An English–Nigerian Pidgin Educational Parallel Corpus}, |
| year = {2026}, |
| publisher = {Hugging Face} |
| } |
