Learning Translation Rules From A Bilingual Corpus

This paper proposes a mechanism for learning pattern correspondences between two languages from a corpus of translated sentence pairs. The proposed mechanism uses analogical reasoning between two translations. Given a pair of translations, the similar parts of the sentences in the source language must correspond the similar parts of the sentences in the target language. Similarly, the different parts should correspond to the respective parts in the translated sentences. The correspondences between the similarities, and also differences are learned in the form of translation rules. The system is tested on a small training dataset and produced promising results for further investigation.

Using a Corpus for Teaching Turkish Morphology

This paper reports on the preliminary phase of our ongoing research towards developing an intelligent tutoring environment for Turkish grammar. One of the components of this environment is a corpus search tool which, among other aspects of the language, will be used to present the learner sample sentences along with their morphological analyses. Following a brief introduction to the Turkish language and its morphology, the paper describes the morphological analysis and ambiguity resolution used to construct the corpus used in the search tool. Finally, implementation issues and details involving the user interface of the tool are discussed.