International Journal of Corpus Linguistics - Volume 5, Issue 2, 2000

In this article, we discuss methodologies to extend computational semantic lexicons in a cost effective way using on-line language resources and savoir faire. First, we introduce the ecology of computational semantic lexicon acquisition, presenting two main methodologies: thesaurus-driven versus corpus-driven. Second, we describe an experiment to extend a semantics-based core lexicon with paradigmatic relations and predict the syntactic behavior of verbs based on their semantics; the automatically derived subcategorizations are first checked against corpora and then manually filtered. These lexicons have been developed within Mikrokosmos, a semantics-based machine translation system.

Corpus linguistics, descriptive, sociolinguistics, and psycholinguistics use corpora and generalise their findings beyond the samples contained in them. That raises the problem of the representativity of the data base and of the application of methods for the presentation of findings. Although this paper originated in the context of the pluricentricity of English in the lexis of mainstream Australian English (mAusE), it was inspired by the current debates about corpus methodology (Kretzschmar et al. 1987). It is based on a large newspaper corpus that extends over a period of six years. It studies the distribution patterns of a small set of lexical items that are derived from Aboriginal languages or relate to Aboriginal concerns. While there appears to be a fairly consistent stable core, these items manifest significant differences in occurrence over the six-year period and in the media outlets and that raises the questions of what a replicate study of these items (or of others) would find and whether a corpus can claim to be representative in the first place.

This paper discusses the approach of developing a sample of printed corpus in Bangla, one of the national languages of India and the only national language of Bangladesh. It is designed from the data collected from various published documents. The paper highlights different issues related to corpus generation, data-file preparation, language analysis, and processing as well as application potentials to different areas of pure and applied linguistics. It also includes statistical studies on the corpus along with some interpretation of the results. The difficulties that one may face during corpus generation are also pointed out.

The research described in this paper is rooted in the endeavors to combine the advantages of corpus-based and rule-based MT approaches in order to improve the performance of MT systems—most importantly, the quality of translation. The authors review the ongoing activities in the field and present a case study, which shows how translation knowledge can be drawn from parallel corpora and compiled into the lexicon of a rule-based MT system. These data are obtained with the help of three procedures: (1) identification of hence unknown one-word translations, (2) statistical rating of the known one-word translations, and (3) extraction of new translations of multiword expressions (MWEs) followed by compilation steps which create new rules for the MT engine. As a result, the lexicon is enriched with translation equivalents attested for different subject domains, which facilitates the tuning of the MT system to a specific subject domain and improves the quality and adequacy of translation.