---
license: mit
---

# BanglaNER
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1uN1WP7MjaBYXKABfhkHGn7EBWm9kd9k9?usp=sharing)
Bangla Name Entity Recognition (NER) is extracting human names from input Bangla string or text. To solve this problem select Spacy pipeline and try 5 experimental approaches.

The experiment is done only using one entity name (person) labeled as PER. After completing the experiment we got the best performance from the spacy transformer-based model.

For more detail please check the experimental details and Best model F1 score is ~.81.05.
# Dataset

Bangla NER data is collected from,

1. banglakit Bangla NER Dataset [Link](https://raw.githubusercontent.com/banglakit/bengali-ner-data/master/main.jsonl)

2. Rifat1493 Bangla NER Dataset [Link](https://github.com/Rifat1493/Bengali-NER/tree/master/Input) 


3. SemEval2022 Bangla NER Dataaset [Link](https://competitions.codalab.org/competitions/36425#learn_the_details)

More Detail about the model check github.

# Reference

1. [Spacy Training Pipelines & Models](https://spacy.io/usage/training)
2. [NER data annotation](https://doccano.github.io/doccano/tutorial/)

3. [BERT Pretrin model ](https://github.com/csebuetnlp/banglabert)
4. [BILOU data formats meaning](https://stackoverflow.com/questions/17116446/what-do-the-bilou-tags-mean-in-named-entity-recognition)
5. [SpaCy 3.1 data format](https://zachlim98.github.io/me/2021-03/spacy3-ner-tutorial)
6. [Tranformer infornation](https://jalammar.github.io/illustrated-transformer/)
7. [Load Gensim WordVectors into spacy pipeline](https://stackoverflow.com/questions/75521069/load-gensim-wordvectors-into-spacy-pipeline)