@inproceedings{stollenwerk-2023-nerblackbox,
title = "nerblackbox: A High-level Library for Named Entity Recognition in Python",
author = "Stollenwerk, Felix",
editor = "Tan, Liling and
Milajevs, Dmitrijs and
Chauhan, Geeticka and
Gwinnup, Jeremy and
Rippeth, Elijah",
booktitle = "Proceedings of the 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS 2023)",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.nlposs-1.20",
doi = "10.18653/v1/2023.nlposs-1.20",
pages = "174--178",
abstract = "We present **nerblackbox**, a python library to facilitate the use of state-of-the-art transformer-based models for named entity recognition. It provides simple-to-use yet powerful methods to access data and models from a wide range of sources, for fully automated model training and evaluation as well as versatile model inference. While many technical challenges are solved and hidden from the user by default, **nerblackbox** also offers fine-grained control and a rich set of customizable features. It is thus targeted both at application-oriented developers as well as machine learning experts and researchers.",
}
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%0 Conference Proceedings
%T nerblackbox: A High-level Library for Named Entity Recognition in Python
%A Stollenwerk, Felix
%Y Tan, Liling
%Y Milajevs, Dmitrijs
%Y Chauhan, Geeticka
%Y Gwinnup, Jeremy
%Y Rippeth, Elijah
%S Proceedings of the 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS 2023)
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F stollenwerk-2023-nerblackbox
%X We present **nerblackbox**, a python library to facilitate the use of state-of-the-art transformer-based models for named entity recognition. It provides simple-to-use yet powerful methods to access data and models from a wide range of sources, for fully automated model training and evaluation as well as versatile model inference. While many technical challenges are solved and hidden from the user by default, **nerblackbox** also offers fine-grained control and a rich set of customizable features. It is thus targeted both at application-oriented developers as well as machine learning experts and researchers.
%R 10.18653/v1/2023.nlposs-1.20
%U https://aclanthology.org/2023.nlposs-1.20
%U https://doi.org/10.18653/v1/2023.nlposs-1.20
%P 174-178
Markdown (Informal)
[nerblackbox: A High-level Library for Named Entity Recognition in Python](https://aclanthology.org/2023.nlposs-1.20) (Stollenwerk, NLPOSS-WS 2023)
ACL