  This article presents the results of the evaluation campaign of language
tools available for fifteen EU-official under-resourced languages. The
evaluation was conducted within the MSC ITN CLEOPATRA action that aims at
building the cross-lingual event-centric knowledge processing on top of the
application of linguistic processing chains (LPCs) for at least 24 EU-official
languages. In this campaign, we concentrated on three existing NLP platforms
(Stanford CoreNLP, NLP Cube, UDPipe) that all provide models for
under-resourced languages and in this first run we covered 15 under-resourced
languages for which the models were available. We present the design of the
evaluation campaign and present the results as well as discuss them. We
considered the difference between reported and our tested results within a
single percentage point as being within the limits of acceptable tolerance and
thus consider this result as reproducible. However, for a number of languages,
the results are below what was reported in the literature, and in some cases,
our testing results are even better than the ones reported previously.
Particularly problematic was the evaluation of NERC systems. One of the reasons
is the absence of universally or cross-lingually applicable named entities
classification scheme that would serve the NERC task in different languages
analogous to the Universal Dependency scheme in parsing task. To build such a
scheme has become one of our the future research directions.
