Automatic Classification of WordNet Morphosemantic Relations

摘要

This paper presents work in progress on a machine learning method for classification of morphosemantic relations between verb and noun synsets. The training data comprises 5,584 verb-noun synset pairs from the Bulgarian WordNet, where the morphosemantic relations were automatically transferred from the Princeton Word-Net morphosemantic database. The machine learning is based on 4 features (verb and noun endings and their respective semantic primes). We apply a supervised machine learning method based on a decision tree algorithm implemented in Python and NLTK. The overall performance of the method reached F_1-score of 0.936. Our future work focuses on automatic identification of morphosemantically related synsets and on improving the classification.