The goal of Automatic (Named) Entity Annotation is to create a small annotated dataset for NER extracted from German domain-specific texts.
To cite the related paper, please use
@inproceedings{Zhukova2021a,
title = {ANEA: Automated (Named) Entity Annotation for German Domain-Specific Texts},
author = {Zhukova, Anastasia and Hamborg, Felix and Gipp, Bela},
year = 2021,
month = {September, 30th},
booktitle = {Proceedings of the 2nd Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE 2021) co-located with JCDL 2021, Virtual Event},
publisher = {CEUR},
address = {Illinois, USA},
doi = {10.6084/m9.figshare.17185373.v2},
url = {http://ceur-ws.org/Vol-3004/paper1.pdf},
editor = {Zhang, Chengzhi and Mayr, Philipp and Lu, Wei and Zhang, Yi}
}
Python 3.8 Required approx. 8Gb of hard memory, 16Gb RAM
Download "numberbatch_voc.txt" from https://drive.google.com/file/d/1Ag3gQUBtmqB-WAGXk67nJwUvMiZ1DdQG/view?usp=sharing and place to
resources/numberbatch
You can either use your own documents stored as a list of strings in a json file, or use a key-word for searching in Wikipedia to get articles to annotate.
Place your file into data folder.
Then execute
pip install -r requirements.txt
python -m spacy download de_core_news_sm
run_anea.py
Follow the instructions to choose a folder with your topic to annotate.
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