Learn More
Most attempts to integrate FrameNet in NLP systems have so far failed because of its limited coverage. In this paper, we investigate the applicability of distributional and WordNet-based models on the task of lexical unit induction , i.e. the expansion of FrameNet with new lexical units. Experimental results show that our distributional and WordNet-based(More)
State-of-the-art semantic role labelling systems require large annotated corpora to achieve full performance. Unfortunately, such corpora are expensive to produce and often do not generalize well across domains. Even in domain, errors are often made where syntactic information does not provide sufficient cues. In this paper , we mitigate both of these(More)
Discourse coherence is an important aspect of natural language that is still understudied in computational linguistics. Our aim is to learn factors that constitute coherent discourse from data, with a focus on how to realize predicate-argument structures (PAS) in a model that exceeds the sentence level. In particular, we aim to study the case of(More)
—The second order extended Kalman filter (EKF2) is based on a second order Taylor expansion of a nonlinear system, in contrast to the more common (first order) extended Kalman filter (EKF1). Despite a solid theoretical ground for its approximation, it is seldom used in applications, where the EKF and the unscented Kalman filter (UKF) are the standard(More)
Generating coherent discourse is an important aspect in natural language generation. Our aim is to learn factors that constitute coherent discourse from data, with a focus on how to realize predicate-argument structures in a model that exceeds the sentence level. We present an important subtask for this overall goal, in which we align predicates across(More)
For many years, the convergence of Internet data services and transport network services based on optical transmission has been at the heart of car-riers' investments and business strategies. Over time, the inherent segmentation of IP and transport networks has created major technology differences, thus impacting their management and operation. In addition,(More)
Current research on linking implicit roles in discourse is severely hampered by the lack of sufficient training resources, especially in the verbal domain: learning algorithms require higher-volume annotations for specific predicates in order to derive valid generalizations, and a larger volume of annotations is crucial for insightful evaluation and(More)
Implicit arguments are a discourse-level phenomenon that has not been extensively studied in semantic processing. One reason for this lies in the scarce amount of annotated data sets available. We argue that more data of this kind would be helpful to improve existing approaches to linking implicit arguments in discourse and to enable more in-depth studies(More)
Software requirements are commonly written in natural language, making them prone to ambiguity, incompleteness and inconsistency. By converting requirements to formal semantic representations, emerging problems can be detected at an early stage of the development process, thus reducing the number of ensuing errors and the development costs. In this paper,(More)