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KennethEnevoldsen authored Apr 29, 2024
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# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: "Augmenty: The cherry on top of your NLP pipeline"
message: "If you use this software, please cite it as below."
type: software
cff-version: "1.2.0"
authors:
- family-names: Enevoldsen
given-names: Kenneth
orcid: "https://orcid.org/0000-0001-8733-0966"
doi: 10.5281/zenodo.11002422
message: If you use this software, please cite our article in the
Journal of Open Source Software.
preferred-citation:
authors:
- family-names: Enevoldsen
given-names: Kenneth
orcid: "https://orcid.org/0000-0001-8733-0966"
identifiers:
- type: url
value: "https://arxiv.org/abs/2312.05520"
description: Arxiv URL
- type: doi
value: 10.5281/zenodo.6675315
description: Zonedo DOI
repository-code: "https://github.com/KennethEnevoldsen/augmenty"
url: "https://kennethenevoldsen.github.io/augmenty/"
abstract: >-
Augmnety is a Python library for structured text
augmentation. It is built on top of spaCy and allows for
augmentation of both the text and its annotations.
Augmenty provides a wide range of augmenters which can be
combined in a flexible manner to create complex
augmentation pipelines. It also includes a set of
primitives that can be used to create custom augmenters
such as word replacement augmenters. This functionality
allows for augmentations within a range of applications
such as named entity recognition (NER), part-of-speech
tagging, and dependency parsing.
keywords:
- nlp
- augmentation
- spacy
- natural language processing
license: MIT
version: 1.4.2
date-released: "2023-12-09"
preferred-citation:
type: article
date-published: 2024-04-27
doi: 10.21105/joss.06370
issn: 2475-9066
issue: 96
journal: Journal of Open Source Software
publisher:
name: Open Journals
start: 6370
title: "Augmenty: A Python Library for Structured Text Augmentation"
url: "https://arxiv.org/abs/2312.05520"
year: 2023
authors:
- family-names: "Enevoldsen"
given-names: "Kenneth"
orcid: "https://orcid.org/0000-0001-8733-0966"
type: article
url: "https://joss.theoj.org/papers/10.21105/joss.06370"
volume: 9
title: "Augmenty: A Python Library for Structured Text Augmentation"

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