Grammar Extraction from Treebanks for Hindi and Telugu

Grammars play an important role in many Natural Language Processing (NLP) applications. The traditional approach to creating grammars manually, besides being labor-intensive, has several limitations. With the availability of large scale syntactically annotated treebanks, it is now possible to automatically extract an approximate grammar of a language in any of the existing formalisms from a corresponding treebank. In this paper, we present a basic approach to extract grammars from dependency treebanks of two Indian languages, Hindi and Telugu. The process of grammar extraction requires a generalization mechanism. Towards this end, we explore an approach which relies on generalization of argument structure over the verbs based on their syntactic similarity. Such a generalization counters the effect of data sparseness in the treebanks. A grammar extracted using this system can not only expand already existing knowledge bases for NLP tasks such as parsing, but also aid in the creation of...

• Type: Conference
• Year: 2010
• Where: LREC
• Authors: Prasanth Kolachina, Sudheer Kolachina, Anil Kumar Singh, Samar Husain, Viswanatha Naidu, Rajeev Sangal, Akshar Bharati
• Keywords: Education, Grammar, Grammar Extraction, LREC 2010, Natural Language Processing