This paper presents research into verb of motion (VOM) constructions in Russian. These constructions are difficult since they involve (i) selection of an appropriate verb (with possible prefixation); (ii) selection of an appropriate preposition; and (iii) selection of an appropriate case for marking the prepositional object. A brief sketch of relevant literature frames the problem. We then disc...

In this paper, the problem of mapping prepositions in the context of machine translation is discussed. For instance, each sense of a polysemous English preposition maps to a different lexical postposition in Hindi. In a fully automatic machine translation system this problem may be resolved in at least two ways-using transfer rules with semantic features or mapping the preposition to an underly...

In this paper, we describe our experiments in preposition disambiguation based on a – compared to a previous study – revised annotation scheme and new features derived from a matrix factorization approach as used in the field of distributional semantics. We report on the annotation and Maximum Entropy modelling of the word senses of two German prepositions, mit (‘with’) and auf (‘on’). 500 occu...

this study investigated the effect of applying the dynamic system theory (dst) and cognitive linguistics (cl) insights into grammar instruction on efl learners’ learning of english prepositions and learner autonomy. sixty iranian efl learners at the lower-intermediate level of language proficiency were randomly assigned to 1 experimental and 1 control group. the 2 groups filled out an autonomy ...

This paper presents a detailed account of prepositional mismatch between our handcrafted verb lexicon and a semantically annotated corpus. The analysis of these mismatches allows us to re ne the lexicon and to create a more robust resource capable of better semantic predictions based on the verb-preposition relations.

In this paper we present results from two pilot studies which show that using the Amazon Mechanical Turk for preposition error annotation is as effective as using trained raters, but at a fraction of the time and cost. Based on these results, we propose a new evaluation method which makes it feasible to compare two error detection systems tested on different learner data sets.

The starting point of this study stems from the two assumptions that are commonly accepted and, to a great extent, proven within cognitive linguistics: 1. members category prepositions bearers autonomous meanings, and 2. prepositional meanings conditioned significantly by concepts pertinent domain space. In light theoretical model semantic representation previously developed author (2022) his r...