A text augmentation tool for named entity recognition.

Last update: Oct 11, 2022

Overview

neraug

This python library helps you with augmenting text data for named entity recognition.

Augmentation Example

Reference from An Analysis of Simple Data Augmentation for Named Entity Recognition

Installation

To install the library:

pip install neraug

Usage

One of the example algorithms: DictionaryReplacement:

>>> from neraug.augmentator import DictionaryReplacement
>>> from neraug.scheme import IOBES

>>> ne_dic = {'Tokyo Big Sight': 'LOC'}
>>> augmentator = DictionaryReplacement(ne_dic, str.split, IOBES)
>>> x = ['I', 'went', 'to', 'Tokyo']
>>> y = ['O', 'O', 'O', 'S-LOC']
>>> x_augs, y_augs = augmentator.augment(x, y, n=1)   
>>> x_augs
[['I', 'went', 'to', 'Tokyo', 'Big', 'Sight']]
>>> y_augs
[['O', 'O', 'O', 'B-LOC', 'I-LOC', 'E-LOC']]

The library supports the following algorithms:

DictionaryReplacement
LabelWiseTokenReplacement
MentionReplacement
ShuffleWithinSegment

and supports the following scheme:

IOB2
IOBES
BILOU

Reference

Appreciate for the following research:

An Analysis of Simple Data Augmentation for Named Entity Recognition

Citation

@misc{neraug,
  title={neraug: A data augmentation tool for named entity recognition},
  author={Hiroki Nakayama},
  url={https://github.com/Hironsan/neraug},
  year={2021}
}

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Releases(v0.1.1)

v0.1.1(Jul 22, 2021)

Remove tokenizer from MentionReplacement
Source code(tar.gz)
Source code(zip)
v0.1.0(Jul 22, 2021)

Source code(tar.gz)
Source code(zip)

A text augmentation tool for named entity recognition.

Related tags

Overview

neraug

Augmentation Example

Installation

Usage

Reference

Citation

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Owner

Hiroki Nakayama

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