Natural Language Learning

This thesis is a small step towards automated learning of natural languages. With the use of a parser that incorporates machine-learning algorithms, our algorithm is able to learn mean-ings of words representing relations in simple sentences, that describe relative positions of two points on a 2D plane. Our SentenceLearner program can create simple sentences describing rela-tions between two points on another 2D plane using data, collected by a statistical parser from sentences given for training, based on n-grams of five words. In this thesis I show that association of simple relations expressed in training sentences with the positional relations of a corresponding pair of points on a 2D plane is possible without the use of any machine-learning algorithm in some circumstances.