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haajidheere/
ErayNet-nirig

sentence-transformers

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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

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)

haajidheere/ErayNet-nirig