A Hybrid Method of Verb Disambiguation in Machine Translation


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 5, No. 3, pp. 681-687, Mar. 1998
10.3745/KIPSTE.1998.5.3.681,   PDF Download:

Abstract

The paper presents a hybrid method for disambiguation of the verb meaning in the machine translation. The presented verb translation algorithm is to perform the concept-based method and the statistics-base method simultaneously. It uses a collocation dictionary, WordNet and the statistical information extracted from corpus. In the transfer phase of the machine translation, it tries to find the target word of the source verb. If it fails, it refers to WordNet to try to find it by calculating word similarities between the logical constraints of the source sentence and those in the collocation dictionary. At the same time, it refers to the statistical information extracted from corpus to try to find it by calculating co-occurrence similarity knowledge. The experimental result shows that the algorithm performs more accurate verb translation than the other algorithms and improves accuracy of the verb translation by 24.8% compared to the collocation-based method.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from September 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[IEEE Style]
M. Y. Jin and M. Palmer, "A Hybrid Method of Verb Disambiguation in Machine Translation," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 5, no. 3, pp. 681-687, 1998. DOI: 10.3745/KIPSTE.1998.5.3.681.

[ACM Style]
Moon Yoo Jin and Martha Palmer. 1998. A Hybrid Method of Verb Disambiguation in Machine Translation. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 5, 3, (1998), 681-687. DOI: 10.3745/KIPSTE.1998.5.3.681.