  This article presents the strategy for developing a platform containing
Language Processing Chains for European Union languages, consisting of
Tokenization to Parsing, also including Named Entity recognition andwith
addition ofSentiment Analysis. These chains are part of the first step of an
event-centric knowledge processing pipeline whose aim is to process
multilingual media information about major events that can cause an impactin
Europe and the rest of the world. Due to the differences in terms of
availability of language resources for each language, we have built this
strategy in three steps, starting with processing chains for the well-resourced
languages and finishing with the development of new modules for the
under-resourced ones. In order to classify all European Union official
languages in terms of resources, we have analysed the size of annotated corpora
as well as the existence of pre-trained models in mainstream Language
Processing tools, and we have combined this information with the proposed
classification published at META-NETwhitepaper series.
