INTRODUCTION: RESEARCH AREA 1. Chinese Semantics 2. Semantic difference related to syntax 3. Module Attribute Representation of Verbal Semantics (MARVS)

AIM/JUSTIFICATION Chinese is full of near-synonymous verbs which are difficult for foreign learners to learn and they are a potential problem for computer translation. MARVS is a representational framework to distinguish meaning of Chinese verbs in their syntax structures. Try to do a little help to Chinese learners and a little bit contribution to computer translation by using MARVS to find out the distinction between “Guan” and “Kan”( both means looking in Chinese).

REFERENCES (1) Huang, Chu-Ren, Kathleen Athens, Li-Li Chang, Keh-Jiann Chen, Mei-Chun Liu, and Mei-Chih Tsai The Module-Attribute Representation of Verbal Semantics: From Semantics to Argument Structure. International Journal of Computational Linguistics and Chinese Language Processing. (2) Liu, Mei-Chun Corpus-based Lexical Semantic Study of Verbs of Doubt: Huayi and Cai in Mandarin. Concentric （ 3 ） Liu, Mei-Chun From Collocation to Event Information: the Case of Mandarin Verbs of Discussion1. Language and Linguistics 4 (3): , (4) Chiang, Ting-Yi, Chou, Ming-Hui, Liu, Mei-Chun A Frame-based Approach to Polysemous Near-synonymy: the Case with Mandarin Verbs of Expression. Journal of Chinese Language and Computing, 15 (3): ( ) (5) Chung, Siaw-Fong and Kathleen Ahrens. Forthcoming. MARVS Revisited: Operationalizing Sense Frequency and MI Values. Language and Linguistics: Lexicon, Grammar and Natural Language Processing. (6) Mei-chun Liu and Ting-yi Chiang The Construction of Mandarin VerbNet: A Frame-based Study of Statement Verbs. LANGUAGE AND LINGUISTICS 9.2: , 2008 （ 7 ） Wang Juan A Corpus Based Study on the Chinese Near- Synonymous Verbs of Running

RESEARCH QUESTIONS Can the two near-synonymous verbs of looking in Chinese be used alternatively in all the contexts? If not, what are their distribution differences? How to explain the differences by using the model of MARVS? (Two more steps will be introduced here)

MATERIALS/INSTRUMENTS Module Attribute Representation of Verbal Semantics (MARVS) Verb---Sense---Eventive Information Share Sense and Mutual Information Value Event Module Event-Internal Attribute Role Module Role-Internal Attribute

METHODOLOGY ---SOURCE The corpus that I would like to use is developed by the Center for Chinese Linguistics of Beijing University. Both modern and classical Chinese data are included in this corpus. For the modern Chinese data, there are both spoken and written data, and the latter just takes a small percentage (0.04%). Now I am also trying to find a Chinese corpus dominated by spoken data.

METHODOLOGY ---PROCEDURE Firstly, all instances of each of the two verbs will be searched for in the corpus. Secondly, these entries of each verb will be classified into different type of syntactic pattern. Thirdly, the aspectual type that is associated with each verb will be examined. Last but not least, I will use the modified MARVS model to explain the differences between the verbs.

METHODOLOGY ---TYPE OF DATA AND ANALYSISMETHODOLOGY ---TYPE OF DATA AND ANALYSIS Data collection: written ones and spoken ones. Beginning period: quantitative approach to analyze data themselves and try to find out their common features. Later period: qualitative approach to explain the differences under the guidance of modified MARVS. TYPE OF DATA AND ANALYSIS

A Corpus Based Study on the Chinese Near- Synonymous Verbs of Looking By Using Modified MARVS Sun He

ANTICIPATED PROBLEMS/LIMITATIONS OF THE STUDY The data I can collect is probably prone to written ones since the spoken ones are hard to access to. Therefore the result will not very comprehensive.

WHAT DO YOU EXPECT TO FIND? Kan probably has the event focus of both the starting and the endpoint of the event while Guan does not. Guan tends to work more with artistic words while Kan can work with more variety kinds of nouns.