cetinsamet / named-entity-recognition

Named-entity recognizer for the English language

named-entity-recognizer

Implementation of a named-entity recognizer for the English language A named-entity recognition model is trained with a corpus containing almost 14,000 English sentences.

Model

Model (mini model) in the repo is trained using mini data which contains only almost 100 English sentences.
Therefore, it does not perform well enough.

I encourage you to train a new model on your own using the corpus in data/ directory.
My training lasted almost 10 minutes on a device with 3,1 GHz Intel Core i7 processor.
Training accuracy was 100% where test accuracy was 97%.

Usage

$python3 ner.py input-sentence

Example

$cd src
$python3 ner.py "Joe Strummer was born in Ankara."
-> Named entity recognizer is loaded.
-> [('Joe', 'B-PER'), ('Strummer', 'I-PER'), ('was', 'O'), ('born', 'O'), ('in', 'O'), ('Ankara', 'B-LOC'), ('.', 'O')]

P.S. Above example is tested with a model trained on corpus in data/ directory(with almost 14,000 English sentences).

Have fun.