International Journal of Corpus Linguistics - Volume 21, Issue 1, 2016

This study extends the theory of local grammars by making the case that local grammars can also be employed to better and more fully describe the patterns of co-selection found in collocational frameworks (Renouf & Sinclair 1991). The term collocational framework was originally used to describe the co-selection of two grammatical words which frame an intervening lexical word. In the present study a more inclusive definition is adopted and the number of intervening words is not limited. While there have been a small number of studies related to collocational frameworks there has been no attempt so far to see whether it is possible to describe their local grammars. To illustrate the feasibility of identifying the local grammars of collocational frameworks, four collocational frameworks are studied here: any … may, may … any, any … shall, and shall … any and their local grammars are identified and discussed.

This paper is an analysis of trajectors (i.e. located entities) in language about fixed durations of TIME. More specifically, trajectors in instances including the English prepositions in or on, or their Swedish equivalents i or på, are analyzed. On the structure of the inverse Moving Observer/Moving Time metaphors (Lakoff & Johnson 1999) instances such as these should be construed relative to a Moving Observer, and trajectors people that move relative to fixed durations of TIME (as reflected in e.g. when we come to launching the 4th edition in early 1990). My analysis, however, suggests that our understanding of TIME through SPACE is more nuanced than suggested by these metaphors. In this specific context, trajectors are not typically people in motion, but rather events or processes located in, or on, unit of time landmarks. My study emphasizes the need to test the systematicity of the mappings proposed by Conceptual Metaphor Theory.

Lectometry is a corpus-based methodology that explores how multiple language-external dimensions shape language usage in an aggregate perspective. The paper combines this methodology with Semantic Vector Space modeling to investigate lexical variability in written Standard English, as sampled in the original Brown family of corpora (Brown, LOB, Frown and F-LOB). Based on a joint analysis of 303 lexical variables, which are semi-automatically extracted by means of a SVS, we find that lexical variation in the Brown family is systematically related to three lectal dimensions: discourse type (informative versus imaginative), standard variety (British English versus American English), and time period (1960s versus 1990s). It turns out that most lexical variables are sensitive to at least one of these three language-external dimensions, yet not every dimension has dedicated lexical variables: in particular, distinctive lexical variables for the real time dimension fail to emerge.

Prescriptive grammarians advise against the use of the quantifier many in informal positive sentences, unless it is modified by too, so, or as. However, because these grammarians may not have conducted a thorough corpus-based analysis, such advice may be unsound. This is why this article attempts to identify the actual constraints on the use of many, by searching corpora for data for many and its competitor a lot of, with plural count nouns in positive sentences. Conducted within the conceptual framework of cognitive linguistics, the analysis suggests that quantities denoted by many are construed as heterogeneous and discrete, hence the relative affinity of many for nouns of place and time, as part of adverbial phrases. This core meaning may also account for many’s relative affinity for personal nouns in subject position. Unlike a lot of, many seems to associate awkwardly with homogeneous substances, which may be why it is rarely found in object noun phrases.

In this article, I provide a brief introduction to the operation and motivation behind the text analysis tool WordSkew. This program, currently available for Windows, is a variant of a typical concordance program. The distinguishing feature of the software is that it allows the user to specify the units of discourse and apposite ways of segmenting the discourse. The results of a search query are then given with respect to each segment. For example, sentences might be divided into ten segments (based on word counts) and the frequency of the search term is then provided for each segment. This process is repeated as required for other textual units.

We present a parallel corpus of German/Swiss German Sign Language train announcements. The corpus is used in a statistical machine translation system that translates from German to Swiss German Sign Language. The output of the translation system is then passed on to an animation system, the result being a sign language avatar representation on a mobile phone. Building the parallel corpus consisted of four steps: translating the written German train announcements into Swiss German Sign Language glosses, signing the announcements in front of a camera on the basis of the gloss transcriptions, notating the signs in the video recordings in a form-based sign language notation system, and adding information about non-manual features. The resulting corpus contains 3,241 sentence pairs, which makes it a large parallel corpus involving sign language.