Automatic Lexical Classification -- Balancing between Machine Learning and Linguistics
Anna Korhonen · Institutional Repositories DataBase (IRDB) · 2009
Abstract. Verb classifications have been used to support a number of practical tasks and applications, such as parsing, information extraction, question-answering, and machine translation. However, large-scale exploitation of verb classes in real-world or domain-sensitive tasks has not been possible because existing manually built classifications are incomprehensive. This paper describes recent and on-going research on extending and acquiring lexical classifications automatically. The automatic approach is attractive since it is cost-effective and opens up the opportunity of learning and tuning lexical classifications for the application and domain in question. However, the development of an optimal approach is challenging, and requires not only expertise in machine learning but also a good understanding of the linguistic principles of lexical classification.