A hybrid representation based simile component extraction

Simile, a special type of metaphor, can help people to express their ideas more clearly. Simile component extraction is to extract tenors and vehicles from sentences. This task has a realistic significance since it is useful for building cognitive knowledge base. With the development of deep neural networks, researchers begin to apply neural models to component extraction. Simile components should be in cross-domain. According to our observations, words in cross-domain always have different concepts. Thus, concept is important when identifying whether two words are simile components or not. However, existing models do not integrate concept into their models. It is difficult for these models to identify the concept of a word. What’s more, corpus about simile component extraction is limited. There are a number of rare words or unseen words, and the representations of these words are always not proper enough. Exiting models can hardly extract simile components accurately when there are low-frequency words in sentences. To solve these problems, we propose a hybrid representation-based component extraction (HRCE) model. Each word in HRCE is represented in three different levels: word level, concept level and character level. Concept representations (representations in concept level) can help HRCE to identify the words in cross-domain more accurately. Moreover, with the help of character representations (representations in character levels), HRCE can represent the meaning of a word more properly since words are consisted of characters and these characters can partly represent the meaning of words. We conduct experiments to compare the performance between HRCE and existing models. The experiment results show that HRCE significantly outperforms current models

Chengyu in Chinese Language Teaching: A preliminary analysis of Italian learners’ data

Chengyu, also known as Chinese four-character idioms, are a type of traditional Chinese idiom, mostly consisting of four characters. They commonly derive from classic Chinese literary sources, including those of the three great philosophical and religious traditions that influenced the entire East Asia cultural sphere: Confucianism, Daoism and Buddhism. Chengyu, therefore, possess a wide range of cultural references, and, from Chinese, spread to the languages of the other countries of the sinosphere, such as Japan and Korea. Although many scholars have emphasized the importance of the acquisition of chengyu, not much attention has been paid to chengyu learning in Chinese Language Teaching research so far. As a preliminary attempt to address this gap, this paper reports the results of two small-scale, exploratory experiments, aimed at investigating Italian learners’ general knowledge of chengyu and their main interpretation strategies, as well as comparing the effectiveness of direct and indirect instruction in chengyu teaching. The experiments involved participants from Bachelor and Master programs of Roma Tre University. The results show a predominant effect of negative transfer from Italian, as well as a better performance of the participants who received indirect instruction