This paper explores the collocational behaviour and semantic prosody of near synonyms from a cross-linguistic perspective. The importance of these concepts to language learning is well recognized. Yet while collocation and semantic prosody have recently attracted much interest from researchers studying the English language, there has been little work done on collocation and semantic prosody on ...

This study examines how different dimensions of corpus frequency data may affect the outcome of statistical modeling of lexical items. The corpus used in our analysis is an elderly speaker corpus in its early development, and the target words are temporal expressions, which might reveal how the speech produced by the elderly is organized. We conduct divisive hierarchical clustering based on two...

the literature on collocations ive do nor find any clear suggestion on how to predict which collocations n,ay be more problematic for the translators and fl tcarners. this article attempts to categorize collocations in six types regardless of their syntactic patterns. front syntactic point of vie1v, this study is limited to adj + n and n + n structures, whiclt contain the most con1n1on collocat...

In this contribution we will argue that negative polarity is a collocational phenomenon that does not follow from other properties of the respective lexical elements. With German data as evidence, we will follow a proposal by van der Wouden and treat Negative Polarity Items (NPIs) as collocates which must be licensed by abstract semantic properties of their contexts. Using a collocation module ...

Identifying collocations in a sentence, in order to ensure their proper processing in subsequent applications, and performing the syntactic analysis of the sentence are interrelated processes. Syntactic information is crucial for detecting collocations, and vice versa, collocational information is useful for parsing. This article describes an original approach in which collocations are identifi...

We describe the SUPERSENSELEARNER system that participated in the English allwords disambiguation task. The system relies on automatically-learned semantic models using collocational features coupled with features extracted from the annotations of coarse-grained semantic categories generated by an HMM tagger.