Chinese Gigaword Corpus Research Articles

From Contact Prevention to Social Distancing: The Co-Evolution of Bilingual Neologisms and Public Health Campaigns in Two Cities in the Time of COVID-19

This article investigates the evolution of social distancing terms in Chinese and English in two geographically close yet culturally distinct metropolitan cities: Hong Kong and Guangzhou. This study of bilingual public health campaign posters during the COVID-19 pandemic focuses on how the evolution of neologisms and linguistic strategies in public health campaigns adapts to different societal contexts. A baseline meaning of the re-purposed linguistic expressions was established according to the BNC corpus for English and the Chinese Gigaword Corpus for Chinese. To establish the link between linguistic expressions and public health events, we converted them to eventive structures using the Module-Attribute Representation of Verbs and added interpersonal meaning interpretations based on Systemic Functional Linguistics. The two cities are found to have taken divergent approaches. Guangzhou prefers “contact prevention” with behavior-inhibiting imperatives and high value modality. Conversely, the original use of “contact prevention” in Hong Kong was gradually replaced by the neologism social distancing in English, triggering competing loan translations in Chinese. In Hong Kong, behavior-encouraging expressions are predominantly used with positive polarity and varying modality and mood devices, which fluctuate to track the epidemic curve of COVID-19. We conclude that lexical evolution interacts with social realities. Different speech acts, prohibition in Guangzhou but advice and warning in Hong Kong, are constructed with a careful bilingual reconfiguration of eventive information, mood, modality, and polarity to tactfully address the social dynamics in the two cities.

A syntagmatic analysis of antonym co-occurrences in Chinese: contrastive constructions and co-occurrence sequences

Antonyms co-occur far more frequently than we might expect to by chance alone. However, few studies have adopted a corpus-based approach to examine antonym co-occurrences in Chinese, and disyllabic antonyms in Chinese have long been ignored in the literature. Therefore, this study turns to the Chinese Gigaword Corpus and includes both monosyllabic and disyllabic pairs for analysis, aiming to identify contrastive constructions in which antonyms in Chinese often co-occur and to examine antonym co-occurrence sequences in Chinese. First, it is found that most functional classes of antonymy in Chinese are associated with specific constructions. Second, a positive antonym in Chinese (e.g., dui ‘right’) usually precedes its negative (e.g., cuo ‘wrong’) counterpart when they co-occur, and the notion of positivity needs to be defined in a broad sense. Third, the behaviour of an antonym pair in Chinese can be influenced by its morphosyllabic structure and some language-external factors such as cognitive functions and socio-cultural values. Our understanding of antonymy in Chinese has been updated, and some striking similarities between Chinese and English in the use of antonyms have also been revealed. It is hoped that the findings of this study will invite more attention to the syntagmatic dimension of antonymy in Chinese.

Toward a Professional Platform for Chinese Character Conversion

Increasing communication among Chinese-speaking regions using respectively traditional and simplified Chinese character systems has highlighted the subtle-yet-extensive differences between the two systems, which can lead to unexpected hindrance in converting characters from one to the other. This article proposes a new priority-based multi-data resources management model, with a new algorithm called Fused Conversion algorithm from Multi-Data resources (FCMD), to ensure more context-sensitive, human controllable, and thus more reliable conversions, by drawing on reverse maximum matching, n -gram-based statistical model and pattern-based learning and matching. After parameter training on the Tagged Chinese Gigaword corpus, its conversion precision reaches 91.5% in context-sensitive cases, the most difficult part in the conversion, with an overall precision rate at 99.8%, a significant improvement over the state-of-the-art models. The conversion platform based on the model has extra features such as data resource selection and n -grams self-learning ability, providing a more sophisticated tool good especially for high-end professional uses.

Collocation, Semantic Prosody, and Near-synonymy: The HELP Verbs in Mandarin Chinese

In this study, our goal was to find out how the verbs 幫忙 bāngmang and 幫助 bāngzhu differ in usage. In particular, we aimed to determine the characteristics of the co-occurrences for the two verbs to investigate whether the verb 幫忙 bāngmang typically takes an event as an object with positive or neutral collocates and whether the verb 幫助 bāngzhu typically takes a person/an organization as an object with negative collocates. Data for the two synonymous verbs were collected from the Chinese GigaWord Corpus using Chinese Word Sketch. As we predicted, our corpus data showed that 幫忙 bāngmang typically took an event as an object and 幫助 bāngzhu typically took a person/an organization as an object, and that the verb 幫助 bāngzhu was more often linked with lexical items that had negative meanings. Based on the results presented, this study has practical implications for second language acquisition, translation, and dictionary compiling.

Sense Prediction Study: Two Corpus-driven Linguistic Approaches

In this study, we propose to use two corpus-driven linguistic approaches for a sense prediction study. We will concentrate on the character similarity clustering approach and the concept similarity clustering approach to predict the senses of non-assigned words by using corpora and tools, such as the Chinese Gigaword Corpus and HowNet. In this study, we will evaluate sense predictions via the sense divisions of Chinese Wordnet (CWN) and Xiandai Hanyu Cidian (Xian Han). Using these corpora, we will determine the clusters of our four target words — chi1 eat, wan2 play, huan4 change, and shao1 burn — in order to predict all possible senses and then evaluate them. This process will demonstrate the viability of the corpus-based approaches.

Event Selection and Coercion of Two Verbs of Ingestion: A MARVS Perspective

Event semantics in general and event type coercion in particular have been a challenging yet rewarding topic in verbal semantics [1]. However, there have been few corpus-based empirical accounts discussing the range of event type coercions based on the lexical meanings of the verbs. In this paper, we explore the possible types of event coercions for two verbs of ingestion in Mandarin Chinese. In particular, we will show that the different types of coercions can be predicted by the bifurcation of event-internal and role-internal attributes proposed in the MARVS theory [2]. Data examined are taken from the Chinese Gigaword Corpus [3, 4] and accessed through Chinese Word Sketch [5].