Word reordering is one of the most difficult aspects of statistical machine translation (SMT),
and an important factor of its quality and efficiency. Despite the vast amount of research …

The main tasks in Example-based Machine Translation (EBMT) comprise of source text
decomposition, following with translation examples matching and selection, and finally …

Divergence of syntactic structures between languages constitutes a major challenge in
using linguistic structure in Machine Translation (MT) systems. Here, we examine the …

In this paper, we propose a novel reordering model based on sequence labeling
techniques. Our model converts the reordering problem into a sequence labeling problem …

This paper studies semantic parsing for interlanguage (L2), taking semantic role labeling
(SRL) as a case task and learner Chinese as a case language. We first manually annotate …

Der kunstvolle Einsatz von Mehrdeutigkeit in der Politik und im Marketing hat viele Vorteile,
weil Mehrdeutigkeit Politikern und Werbeagenturen dabei helfen kann, zwischen mehreren …

Esta tese propõe um recurso léxico de verbos com anotação de papéis semânticos,
denominado VerbLexPor, baseado em recursos como VerbNet, PropBank e FrameNet. As …

Most of the statistical machine translation (SMT) systems suffer from lack of proper
understanding about the meaning of input sentence, confusion of semantic roles or semantic …

This paper presents a lexical resource developed for Portuguese. The resource contains
sentences annotated with semantic roles. The sentences were extracted from two domains …

Word reordering is one of the most difficult aspects of statistical machine translation (SMT),
and an important factor of its quality and efficiency. Despite the vast amount of research …