International Journal of Corpus Linguistics - Volume 15, Issue 1, 2010

Corpus-based translation studies focus on translation as a product by comparing comparable corpora of translational and non-translational texts. A number of distinctive features of translational English in relation to native English have been uncovered. Nevertheless, research of this area has so far been confined largely to translational English translated from closely related European languages. If the features of translational language that have been reported on the basis of translated English are to be generalized as ‘translation universals’, it is of vital importance to find supporting evidence from non-European languages. Clearly, evidence from “genetically” distinct language pairs such as English and Chinese is arguably more convincing, if not indispensable. This article explores potential features of translational Chinese on the basis of two balanced monolingual comparable corpora of translated and native Mandarin Chinese. The implications of the study for translation universal hypotheses are also discussed.

A signalling noun is the use of an abstract noun the full meaning (realisation) of which can only be made specific by reference to its linguistic context. Examples of nouns which can function as signalling nouns are attitude, consequence, difficulty, effect, process, reason and result. The realisation of a signalling noun may occur across clauses or within the clause. Using the ICLE Locness (L1 writers) corpus as a reference corpus and a learner English corpus written by Cantonese-speaking learners of English, this paper presents a comparison of the use of signalling nouns by these two L1 and L2 writer groups. Use of different functions, realisation patterns and selection and range of individual nouns are compared. In this way a profile is built up of the use of signalling nouns by the two target groups and areas for pedagogic intervention are identified.

Using the Corpus of Contemporary American English as the source data and employing a corpus-based behavioral profile (BP) approach, this study examines the internal semantic structure of a set of five near-synonyms (chief, main, major, primary, and principal).1 By focusing on their distributional patterns, especially the typical types of nouns that they each modify, the study has identified several important fine-grained semantic and usage differences among the five near-synonyms and produced a meaningful delineation of their internal semantic structure. Some of the findings of the study challenge several existing understandings of these adjectives’ meanings and usage patterns. Furthermore, the results of the study have affirmed (i) the theory and applicability of the BP approach for studying the semantic and usage patterns of synonyms in a set, and (ii) previous research findings about the co-occurrents of adjectives that best capture the essence of the semantics of adjectives, especially attributive adjectives.

There are no grammatical limits on multiple final embedding of clauses. But converging corpus data from English, Finnish, German and Swedish show that multiple final embedding is avoided at levels deeper than three levels from the main clause in syntactically simple varieties, and at levels deeper than five levels in complex varieties. The frequency of every successive level of final embedding decreases by a factor of seven down to levels 4–5. Only relative clauses allow free self-embedding, within the limits just mentioned. These restrictions are regularities of language use, stylistic preferences related to the properties of various types of discourse. Ultimately they are explained by cognitive and other properties of the language processing mechanisms. The frequencies of final embedding depths in modern languages such as English and Finnish is not accidental. Ancient Greek had reached this profile by 300 BC, suggesting cross-linguistic generality of the preferences.

Annotations are an important resource in corpus-based linguistic research. In fact, the most important feature of a modern signed language corpus should be that it has been annotated rather than simply transcribed. Digital multi-media annotation software can now transform language recordings into machine-readable texts using gloss-based annotations without it first being necessary to transcribe these utterances, provided that sign tokens are identified and discriminated according to type. Further annotations can subsequently be appended to these units. However, unique identifiers of sign types (or ‘ID-glosses’) can only be used if a comprehensive reference lexical database of the language already exists. In order to create a basic multi-purpose reference signed language corpus, therefore, linguists should prioritize annotation using ID-glosses above transcription. The effort expended in creating a transcription that does not facilitate the unique identification of sign types will not result in a machine-readable corpus in any meaningful sense, contrary to expectations.