Sense disambiguation for prepositions is used within a paraphrase recognition system. ‘With’ is chosen to explore our approach of using information from WordNet (hypernym and meronym relations) and LCS (verb lexical information); similar concepts can be used for other prepositions. This paper describes the senses of ‘with’, the disambiguation model, evaluation process, and results.

English prepositions are extremely frequent and extraordinarily polysemous. In some usages they contribute information about spatial, temporal, or causal roles/relations; in other cases they are institutionalized, somewhat arbitrarily, as case markers licensed by a particular governing verb, verb class, or syntactic construction. To facilitate automatic disambiguation, we propose a general-purp...

Function tags mapped to fewer than 20 supersense-tagged prepositions overall are not displayed. (This accounts for why the bars are not strictly decreasing in width.) Numbered arguments tagged with VPC are mapped to Direction in 8 instances. AM-LVB is mapped to Purpose in 8 instances, while AM-CXN is the dominant function tag mapped to Scalar/Rank (18 instances). Distribution of PropBank functi...

We explore some Web-based methods to differentiate strings of words corresponding to Spanish prepositional phrases that can perform either as a regular prepositional phrase or as idiomatic prepositional phrase. The type of these Spanish prepositional phrases is preposition–nominal phrase–preposition (P−NP−P), for example: por medio de ‘by means of’, a fin de ‘in order to’, con respecto a ‘with ...

Representation and Prediction Features Initial experiments showed that replacing prepositions by simple place-holders decreases the translation quality. As an extension to the basic approach with plain place-holders, we thus experiment with enriching the place-holders such that they contain more relevant information and represent the content of a preposition while still being in an abstract for...

In this paper, we describe the University of Illinois system that participated in Helping Our Own (HOO), a shared task in text correction. We target several common errors, such as articles, prepositions, word choice, and punctuation errors, and we describe the approaches taken to address each error type. Our system is based on a combination of classifiers, combined with adaptation techniques fo...

A network was trained by back propagation to map locative expressions of the form "noun-preposition-noun" to a semantic representation, as in Cosic and Munro (1988). The network's performance was analyzed over several simulations with training sets in both English and German. Translation of prepositions was attempted by presenting a locative expression to a network trained in one language to ge...