Tokenizing on scale. Preprocessing large text corpora on the lexical and sentence level.

By September 7, 2022,
Page 208-221
Author Nils Diewald, Marc Kupietz, Harald Lüngen
Title Tokenizing on scale. Preprocessing large text corpora on the lexical and sentence level.
Abstract When comparing different tools in the field of natural language processing (NLP), the quality of their results usually has first priority. This is also true for tokenization. In the context of large and diverse corpora for linguistic research purposes, however, other criteria also play a role – not least sufficient speed to process the data in an acceptable amount of time. In this paper we evaluate several state-­of-the-­art tokenization tools for German – including our own – with regard to theses criteria. We conclude that while not all tools are applicable in this setting, no compromises regarding quality need to be made.
Session Poster
Keywords Corpora, tokenization, German, software
BibTex
@inproceedings{euralex_mannheim_tokenizing_2022,
address = {Mannheim},
title = {Tokenizing on {Scale}.preprocessing {Large} {Text} {Corpora} on the {Lexical} and {Sentence} {Level}.},
isbn = {978-3-937241-87-6},
shorttitle = {Euralex (2022)},
url = {},
language = {eng},
booktitle = {Dictionaries and {Society}. {Proceedings} of the {XX} {EURALEX} {International} {Congress}},
publisher = {IDS-Verlag},
author = {Diewald, Nils and Kupietz, Marc and Lüngen, Harald},
editor = {Klosa-Kückelhaus, Annette and Engelberg, Stefan and Möhrs, Christine and Storjohann, Petra},
year = {2022},
pages = {208--221},
}
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