Augmented Comparative Corpora and Monitoring Corpus in Chinese: LIVAC and Sketch Search Engine Compared

The increasing availability of numerous corpora has significantly contributed to the understanding of words in terms of their underlying semantic structures and lexical networks (e.g. COBUILD, WordNet etc.). Through data mining and information retrieval, research in this area has vastly expanded our appreciation that what constitutes lexical knowledge goes beyond synonymy, hyponymy, metonymy, meronymy, grammatical and other collocations. Furthermore, they are fundamental to a universalistic conceptual base of ontologies and knowledge representation which are often enriched by deeper and newer analysis. In this context, each language foregrounds specific features or nodes within this knowledge base by usually non-uniform means. At the same time, the arrival of the age of Big Data has attracted extensive studies on the actual and dynamic use of language as contextualized (ala. Jakobson 1960) within a given society, especially through the mass media. What are foregrounded in this medium tend to have graded cognitive saliency characterizing members of the common speech community, and such shared knowledge is usually at great variance with the thesaurus approach and show noticeable localized features. It is proposed here that the two kinds of knowledge (thesauric vs cognitive-cultural) complement each other in human cognition, and are integral to it. We draw on two large Chinese media databases Sketch (2.1 billion character tokens1) and LIVAC (550 million character tokens2) for illustration and discussion. The Sketch Engine in Chinese shows how apple is, as expected, primarily related to orange, peach, fruit, vegetable, food etc. At the