Extracting Bilingual Persian Italian Lexicon from Comparable Corpora Using Different Types of Seed Dictionaries
Table 1: Number of entries and mutual words with DicEx of dictionaries used in our Experiments
['Dictionary Name', 'Entries', 'Mutual words']
The parallel corpus-based lexicon, DicPa was a word-to-word sub-part of a translation table, extracted with Giza++. Our parallel corpus contains about 29,000 sentences in both the Persian and Italian languages. When more than one definition was found for a word, the first one is selected and the others are discarded. Finally, the top 40,000 entries of the translation table with a high probability are selected as the new dictionary. As we expected, this could increase efficiency slightly. However, as discussed prior, and because of the vast differences between the structure of Italian and Persian languages, this improvement is very small and could be negligible as a conclusion. According to results, and our expectation, the DicEx has better outcome despite its small size compared with the other dictionaries. A reason is the high accuracy of DicEx as it is a handmade dictionary. We could consider it a 100% accurate dictionary. The experimental results show that DicPi has a slightly better efficiency in comparison with parallel corpora based dictionary DicPa. The authors conclude that the reason is the limitation of our parallel Persian-Italian corpus used to create a translation table. Therefore we have selected some unimportant words that are not translation decisive. If we had enough parallel corpora, this conclusion could be supported or rejected strongly. ’s mutual words with DicEx. This issue could be used to predict the accuracy order in our work.