DocumentCode :
3108901
Title :
Sense disambiguation of simple prepositions in English to Kannada Machine Translation
Author :
Parameswarappa, S. ; Narayana, V.N.
Author_Institution :
Dept. of Comput. Sci. & Eng., Malnad Coll. of Eng., Hassan, India
fYear :
2012
fDate :
18-20 July 2012
Firstpage :
203
Lastpage :
208
Abstract :
The preposition sense disambiguation is a critical task in any reliable Machine Translation (MT) system. The pervasive use of preposition or its equivalent in most of the languages makes it a crucial element during translation. Unlike English, there is no concept of preposition in Kannada. English prepositions are translated to Kannada by attaching appropriate inflections to the head noun of the prepositional phrase. Further post-positional words may also appear in Kannada translation for some prepositions. The choice of the appropriate post-positional word depends on the WordNet synset information of the head noun. The paper proposes an algorithm to disambiguate sense of a simple preposition in English to Kannada MT. It uses properties of the head noun and complement of the preposition for disambiguation. To the best of our knowledge, this is the first attempt towards introducing an algorithm to disambiguate sense of the preposition during English to Kannada MT. Experiments were conducted and the result obtained has been described. The performance of an algorithm is proved to be reliable and scalable.
Keywords :
language translation; natural language processing; English; Kannada machine translation; MT; WordNet synset information; head noun; post-positional words; preposition sense disambiguation; prepositional phrase; simple prepositions; Algorithm design and analysis; Context; Dictionaries; Magnetic heads; Pragmatics; Reliability; Semantics; Dictionary; Kannada postpositions; Machine Translation; Prepositions; Rule file; WordNet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Science & Engineering (ICDSE), 2012 International Conference on
Conference_Location :
Cochin, Kerala
Print_ISBN :
978-1-4673-2148-8
Type :
conf
DOI :
10.1109/ICDSE.2012.6282320
Filename :
6282320
Link To Document :
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