---
language:
  - so
  - en
  - it
license: cc-by-4.0
library_name: sentence-transformers
tags:
  - semantic-search
  - lexical-retrieval
  - somali
  - multilingual
  - dictionary
  - terminology
model_index:
  - name: Eraynet-nirig
    results:
      - task:
          type: text-retrieval
        metrics:
          - type: retrieval_map
            value: N/A (baseline model)
---

# Eraynet-nirig

Eraynet-nirig is a baseline semantic retrieval model for Somali lexical search. It supports Somali, English, and Italian queries over a structured Somali dictionary dataset.

## Overview

This model uses sentence embeddings to perform semantic search across lexical entries containing:

- abbreviation
- Somali term
- Italian gloss
- English gloss
- domain metadata

It is designed as a baseline retrieval system for Somali language technology, terminology search, and dictionary lookup.

## Model Details

- **Model**: paraphrase-multilingual-MiniLM-L12-v2 (fine-tuned/used for embedding)
- **Embedding Dimension**: 384
- **Training Data**: 73 structured Somali lexical entries
- **Languages**: Somali, English, Italian

## Features

- Exact and semantic lexical retrieval
- Multilingual query support: Somali, English, Italian
- Similarity scoring (cosine similarity)
- Confidence labels: high (≥0.7), medium (≥0.5), low (<0.5)
- Top-k results (default: 5)
- Domain-aware search

## Files

- `build_embeddings.py`: builds vector embeddings from the lexical dataset
- `search.py`: runs semantic search with confidence scoring
- `ai_model/embeddings.npy`: stored embeddings (NumPy format)
- `ai_model/search_data.csv`: structured lexical entries

## Example Usage

```python
from search import search

# Search for a term
results = search("medicine")
print(results)
```

Example output:

```
rank    somali   english   italian   domain    similarity_score confidence_label
1       Daawo    medicine  medicina  medicine  0.8542            high
2       ...      ...       ...       ...       ...              ...
```

## Example Queries

- `medicine` → `Daawo`
- `politics` → `siyaasad`
- `botany` → `Botani`

## Installation

```bash
pip install -r requirements.txt
```

## Requirements

- sentence-transformers
- pandas
- numpy
- scikit-learn
- fastapi (optional, for API)
- uvicorn (optional, for API)

## Intended Use

This model is suitable for:

- Somali dictionary search
- terminology lookup
- NLP preprocessing support
- lexical search in multilingual Somali applications

## Limitations

- Small baseline dataset (73 entries)
- Not a generative model
- Not a translation model
- Similarity scores are embedding-based, not calibrated probabilities
- Confidence labels are based on similarity thresholds, not statistical certainty

## Future Work

- expand dataset size with cleaned dictionary entries
- add part-of-speech tagging
- add richer domain annotations
- support example sentence retrieval
- train a Somali-English translation model from parallel sentence pairs

## Version

- **v0.1**: Current baseline - 73 entries, multilingual semantic retrieval

## Citation

If you use this model, please cite:

```
Eraynet-nirig: Somali Multilingual Lexical Retrieval Baseline (2026)
```