A New Massive Multilingual Dataset for High-Performance Language
  Technologies
Ona de Gibert Graeme Nail Nikolay Arefyev Marta Bañón Jelmer van der Linde Shaoxiong Ji Jaume Zaragoza-Bernabeu Mikko Aulamo Gema Ramírez-Sánchez Andrey Kutuzov Sampo Pyysalo Stephan Oepen Jörg Tiedemann
We present the HPLT (High Performance Language Technologies) language
resources, a new massive multilingual dataset including both monolingual and
bilingual corpora extracted from CommonCrawl and previously unused web crawls
from the Internet Archive. We describe our methods for data acquisition,
management and processing of large corpora, which rely on open-source software
tools and high-performance computing. Our monolingual collection focuses on
low- to medium-resourced languages and covers 75 languages and a total of ~5.6
trillion word tokens de-duplicated on the document level. Our English-centric
parallel corpus is derived from its monolingual counterpart and covers 18
language pairs and more than 96 million aligned sentence pairs with roughly 1.4
billion English tokens. The HPLT language resources are one of the largest open
text corpora ever released, providing a great resource for language modeling
and machine translation training. We publicly release the corpora, the
software, and the tools used in this work.