It is often difficult to collect many examples for low-frequency words from a single general purpose corpus. In this paper, I present a method of building a database of Japanese adjective examples from special purpose Web corpora (SPW corpora) and investigates the characteristics of examples in the database by comparison with examples that are collected from a general purpose Web corpus (GPW corpus). My proposed method construct a SPW corpus for each adjective considering to collect examples that have the following features: (i) non-bias, (ii) the distribution of examples extracted from every SPW corpus bears much similarity to that of examples extracted from a GPW corpus. The results of experiments shows the following: (i) my proposed method can collect many examples rapidly. The number of examples extracted from SPW corpora is more than 8.0 times (median value) greater than that from the GPW corpus. (ii) the distributions of co-occurrence words for adjectives in the database are similar to those taken from the GPW corpus.

Compilation of a 100 million words balanced corpus called the Balanced Corpus of Contemporary Written Japanese (or BCCWJ) is underway at the National Institute for Japanese Language and Linguistics. The corpus covers a wide range of text genres including books, magazines, newspapers, governmental white papers, textbooks, minutes of the National Diet, internet text (bulletin board and blogs) and so forth, and when possible, samples are drawn from the rigidly defined statistical populations by means of random sampling. All texts are dually POS-analyzed based upon two different, but mutually related, definitions of ‘word.’ Currently, more than 90 million words have been sampled and XML annotated with respect to text-structure and lexical and character information. A preliminary linear discriminant analysis of text genres using the data of POS frequencies and sentence length revealed it was possible to classify the text genres with a correct identification rate of 88% as far as the samples of books, newspapers, whitepapers, and internet bulletin boards are concerned. When the samples of blogs were included in this data set, however, the identification rate went down to 68%, suggesting the considerable variance of the blog texts in terms of the textual register and style.