Learning a Second Language

Abstract

We present a system, called IMMIGRANT, which learns rules about the grammar of a second language from instructions. We explore the implications of this task on the representation of linguistic knowledge in a natural language understanding system. We conclude that the internal representation of linguistic knowledge used in IMMIGRANT, which is unification-based, is more amenable to language learning from instructions than other representation schemes.