Semantic representation is receiving growing attention in NLP in the past few years, and
many proposals for semantic schemes (eg, AMR, UCCA, GMB, UDS) have been put forth …

Word alignments are useful for tasks like statistical and neural machine translation (NMT)
and cross-lingual annotation projection. Statistical word aligners perform well, as do …

Abstract Starting in 2006, the European Commission's Joint Research Centre and other
European Union organisations have made available a number of large-scale highly …

Viable cross-lingual transfer critically depends on the availability of parallel texts. Shortage
of such resources imposes a development and evaluation bottleneck in multilingual …

Cross-language learning allows us to use training data from one language to build models
for a different language. Many approaches to bilingual learning require that we have word …

Linguistic typology aims to capture structural and semantic variation across the world's
languages. A large-scale typology could provide excellent guidance for multilingual Natural …

In this paper, we present the NewsReader MEANTIME corpus, a semantically annotated
corpus of Wikinews articles. The corpus consists of 480 news articles, ie 120 English news …

Although over 100 languages are supported by strong off-the-shelf machine translation
systems, only a subset of them possess large annotated corpora for named entity …

Many intelligent systems in business, government or academy process natural language as
an input during inference or they might even communicate with users in natural language …

Meaning Representation (AMR) is a popular formalism of natural language that represents
the meaning of a sentence as a semantic graph. It is agnostic about how to derive meanings …