Decategorialization and Chinese nouns

This chapter explores the interaction between semantic change and morphosyntactic decategorialization in the light of the development of classifiers and measure words in Chinese. The vast majority of both classifiers and measure words ultimately derive from independent nouns. Börjars and Payne argue that the decategorialization which measure words have undergone is strikingly unusual in that they have lost the full modificational properties of independent nouns without any accompanying semantic reduction: a measure word maintains its nominal meaning. On the other hand, classifiers lose both the independent semantics and morphosyntax of independent nouns, but because their development proceeds by analogy with that of measure words, they reacquire the same very limited potential for modification. Modelling these diachronic developments from an LFG perspective, they show that, while each individual stage has its own motivation, the end result is an interesting decoupling of the semantic and syntactic aspects of change.

Evaluation of taxonomic and neural embedding methods for calculating semantic similarity

Modelling semantic similarity plays a fundamental role in lexical semantic applications. A natural way of calculating semantic similarity is to access handcrafted semantic networks, but similarity prediction can also be anticipated in a distributional vector space. Similarity calculation continues to be a challenging task, even with the latest breakthroughs in deep neural language models. We first examined popular methodologies in measuring taxonomic similarity, including edge-counting that solely employs semantic relations in a taxonomy, as well as the complex methods that estimate concept specificity. We further extrapolated three weighting factors in modelling taxonomic similarity. To study the distinct mechanisms between taxonomic and distributional similarity measures, we ran head-to-head comparisons of each measure with human similarity judgements from the perspectives of word frequency, polysemy degree and similarity intensity. Our findings suggest that without fine-tuning the uniform distance, taxonomic similarity measures can depend on the shortest path length as a prime factor to predict semantic similarity; in contrast to distributional semantics, edge-counting is free from sense distribution bias in use and can measure word similarity both literally and metaphorically; the synergy of retrofitting neural embeddings with concept relations in similarity prediction may indicate a new trend to leverage knowledge bases on transfer learning. It appears that a large gap still exists on computing semantic similarity among different ranges of word frequency, polysemous degree and similarity intensity.

The Meanings and Structural Forms of the Measure Word for Nouns in Chinese and Vietnamese

In the field of language research, the measure word is an interesting research topic. In the world language, some languages have measure words, some languages have not. Both Chinese and Vietnamese belong to the language rich in measure words, but due to the differences in language system, cognition and cultural color, there are some differences in the expression of their syntactic structure of the measure word for noun. This study starts from the comparison of Chinese and Vietnamese languages, focusing on the meaning and structure of the measure word for noun commonly used in Chinese and Vietnamese, in order to find the similarities and differences between them.

Answer Evaluation of Short Descriptive Questions

Reforms in the educational system emphasize more on continuous assessment. The descriptive examination test paper when compared to objective test paper acts as a better aid in continuous assessment for testing the progress of a student under various cognitive levels at different stages of learning. Unfortunately, assessment of descriptive answers is found to be tedious and time-consuming by instructors due to the increase in number of examinations in continuous assessment system. In this chapter, an attempt has been made to address the problem of automatic evaluation of descriptive answer using vector-based similarity matrix with order-based word-to-word syntactic similarity measure. Word order similarity measure remains as one of the best measures to find the similarity between sequential words in sentences and is increasing its popularity due to its simple interpretation and easy computation.

Automaticity in the reading circuitry

Skilled reading requires years of practice associating visual symbols with speech sounds. Over the course of the learning process, this association becomes effortless and automatic. Here we test whether automatic activation of spoken-language circuits in response to visual words is a hallmark of skilled reading. Magnetoencephalography was used to measure word-selective responses under multiple cognitive tasks (N = 42, 7-12 years of age). Even when attention was drawn away from the words by performing an attention-demanding fixation task, strong word-selective responses were found in a language region (i.e., superior temporal gyrus) starting at ~300 ms after stimulus onset. Critically, this automatic word-selective response was indicative of reading skill: the magnitude of word-selective responses correlated with individual reading skill. Our results suggest that automatic recruitment of spoken-language circuits is a hallmark of skilled reading; with practice, reading becomes effortless as the brain learns to automatically translate letters into sounds and meaning.

Mastering Mandarin Endocentric Phrases: A Five-Step Technique

Mandarin Endocentric Phrases (MEP) is a type of Mandarin phrase which is classified according to its internal structure. It is formed by two components which share a [modifier-head word] relationship. The modifier component precedes the head word it modifies. The role of the modifier is to describe or limit the head word. The Five-Step Technique is a simplified method of arranging words to form MEP. It helps non-native speakers to master the process of sequencing MEP. This technique is informed by findings from research on error analy-sis in the use of MEP among Malay students in Universiti Teknologi MARA (UiTM) Shah Alam campus in 2019. UiTM Malay students are influenced by their mother tongue which is the Malay language when they learn the MEP, thus they often make mistakes in the construction and translation of MEP. This Five-Step technique delineates the cor-rect sequence of MEP into five parts, starting from the demonstrative pronouns, followed by the measure word, modifier or adjective, parti-cle “de” and finally the noun or object. This technique will enable stu-dents to produce error-free MEPs and instinctively build their motiva-tion to master the language. Ideally, Mandarin teachers can use this innovative teaching approach to create an interactive and collabora-tive learning partnership in the Mandarin classroom.

The Syntax of the Abstract-type Measurement Construction in Mandarin Chinese

This paper investigates a special sub-type of measurement construction in Mandarin Chinese, namely the [Num-measure word-de-N] construction where the N is an abstract dimension-denoting noun. Evidence is presented to show that the abstract-type [Num-measure word-de-N] should be fundamentally distinguished from the quantifying-/modifying-type [Num-measure word-de-N], in which the [Num-measure word] sequence serves to quantize/modify a semantically concrete, entity-denoting N. At the interpretive level, this paper claims that the abstracttype [Num-measure word-de-N] is semantically definite. At the syntactic level, a clausal analysis within the framework of the Predicate Inversion theory is pursued to account for the derivation of the abstract-type measurement construction. Last, it is proposed that the word order distinction between the Chinese abstracttype measurement construction, which is N-final, and its English counterpart, where the N linearly precedes [Num-measure word], can be explained in terms of a parametric variation with respect to the (non-)application of N-raising after Predicate Inversion.

Structure of numerals and classifiers in Chinese

It is controversial whether a classifier (C) or measure word (M) in Chinese forms a constituent first with Num (numeral) or N in a [Num C/M N] phrase. This paper reviews evidence for the [Num C/M] constituency from modern Chinese and then provides evidence from historical and typological perspectives. Under the [Num C/M] constituency, not only the C/M word orders attested in Chinese history, but also all those attested elsewhere, can be straightforwardly accounted for by the head parameter, while such simplicity is unattainable under the [C/M N] constituency. In addition, fresh evidence is obtained from the internal word order within a complex numeral; e.g. san-shi ‘30’ is base-final, with n (3) and base (10) entering into a multiplicative function, 3×10. The same multiplicative function exists between Num and C/M, e.g. san-duo hua ‘3 C flower’ = 3×1 flower, and san-da hua ‘3 dozen flower’ = 3×12 flower. C/M and bases are thus unified as multiplicands, an insight further supported by the consistent correlation between the base-final order and the C/M-final order throughout the history of Chinese. A closer examination of the 103 classifier languages in Greenberg (1990[1978]) further reveals that, among the 52 languages whose numeral systems and C/M word orders can be obtained, the synchronization between the numeral base and C/M is nearly universal. The base-C/M unification as multiplicands and base-C/M synchronization in word order strongly suggest that Num and C/M form a single constituent.