DocumentCode :
3452363
Title :
A class-based acceptability measure for persian light verb constructions
Author :
Taslimipoor, Shiva ; Fazly, Afsaneh ; Hamzeh, Ali
Author_Institution :
Electerical & Comput. Eng., Shiraz Univ., Shiraz, Iran
fYear :
2012
fDate :
2-3 May 2012
Firstpage :
250
Lastpage :
255
Abstract :
Light verb constructions (LVCs), also known as compound verbs, require spacial treatment within a computational system. Recently, there has been some work on the automatic identification of LVCs, in resource-rich languages, such as English. Our goal is to adapt such existing techniques for the automatic treatment of LVCs in an under-resourced language, such as Persian. We focus on the most common subclass of Persian LVCs which are noun+verb constructions. LVCs are often formed semi-productively: Although a light verb occurs with a wide range of nouns, it tends to productively combine with certain semantic classes to form LVCs. We expand an existing measure of determining LVC acceptability (for English) to make explicit use of semantic classes of nouns (in Persian). We show that this new class-based acceptability measure outperforms the original measure, when applied to Persian candidate LVCs.
Keywords :
natural language processing; English; Persian LVC; Persian light verb constructions; class-based acceptability measure; compound verbs; noun semantic class; noun-verb constructions; resource-rich languages; underresourced language; Educational institutions; Electronic mail; Estimation; Frequency estimation; Semantics; Vectors; Light Verb Constructions; Multiword Expressions; Natural Language Processing; Semi-productivity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Signal Processing (AISP), 2012 16th CSI International Symposium on
Conference_Location :
Shiraz, Fars
Print_ISBN :
978-1-4673-1478-7
Type :
conf
DOI :
10.1109/AISP.2012.6313753
Filename :
6313753
Link To Document :
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