Part-of-speech studies in Chinese

Abstract

This paper studies parts of speech in Chinese on data taken from the Modern Chinese Dictionary (5th edition). First, the part-of-speech polyfunctionality (ambiguity) of words is determined; then the corresponding distribution and rank-frequency sequence are analysed. The Waring and right truncated modified Zipf-Alekseev distributions are successfully fitted to the data. Second, the 121 patterns that the total 3742 polyfunctional words yield are presented. The polyfunctionality of patterns distributes according to the positive Cohen-binomial distribution, while the rank-frequency sequence abides by the negative hypergeometric distribution. Third, we discuss the mechanism behind the polyfunctionality phenomenon: Chinese words diversify in the dimension of their function but not in their form as can be expected from an analytic language. The Popescu-Altmann function captures the distribution of the variants of each part of speech. Fourth, we analyse the polyfunctionality distributions of individual parts of speech. Out of the 12 parts of speech which the dictionary distinguishes, six can be modelled by the Poisson distribution, four by the mixed Poisson, and two by the Singh-Poisson distribution. In order to obtain a general form, we apply the mixed Poisson distribution for all the parts of speech by controlling one parameter. We make a first attempt to plot the polyfunctionality distributions of individual parts of speech in Ord's system, which surprisingly shows approximately a hyperbola.

A Quantitative Study on English Polyfunctional Words

“…which is proved to be the best model for diversification variants in Wang (2016). The fitting results are shown in Table 5 and Figure 3, mostly acceptable except the conjunction group obtaining R² = 0.6578.…”

“…). Later studies on the polyfunctionality distribution model include Wang (2016), which adopts the Modern Chinese Dictionary (the 5th edition), and Wang & Guo (2018), which adopts CELEX dictionary data (Baayen et al, 1995) from German, Dutch, and English. The results show the Waring distribution -…”

“…Since the article group consists of only three data points (Table 4), it is insufficient to fit a three-parameter model like extended positive binomial distribution. We tried other models with fewer parameters, such as the binomial distribution, because the extended positive binomial belongs to the binomial family, and Shenton-Skees-geometric and Waring, which are reported to capture polyfunctionality distributions by Fan and Altmann (2008) and Wang (2016) respectively. For such a small data set, we use the χ²-test and its p-value instead of the discrepancy coefficient C, which is applied only when the sample is large and χ²-test loses its reliability (Macǔtek & Wimmer, 2013).…”

“…For example, in the sentence A canner can can a can, the first can is a modal verb which means "be able to", the second can is a verb which means "to preserve food by putting it in a can", the last can is a noun which means "a metal container". Linguists call this class cleavage (Bloomfield, 1933), multiple class membership (Bloomfield, 1933;Allerton, 1979;Biber, 1999;Hudson & Hudson, 2007;Jackson & Amvela, 2007;Jackson, 1988;Nida, 1948), multifunctionality (Harris, 1946;Braun, 2009), decategorization (Hopper & Thompson, 1984), intercategorial polysemy (Zawada, 2005), zeroderivation (Kastovsky, 2005), transcategorization (Halliday & Matthiessen, 2006), heterosemy (Enfield, 2006), conversion (Balteiro, 2007), word class expansion (Fan & Altmann, 2008) and polyfunctionality (Wang, 2016). In this paper, we follow the terminology from Wang (2016): words that have more than one part of speech are called polyfunctional words, while words with only one part of speech are called monofunctional words; the number of parts of speech they have is referred to as polyfunctionality (PF).…”