Abstract
The lexicon has emerged from the study of computational linguistics as a fundamental resource that enables a variety of linguistic processes to operate in the course of tasks ranging from language analysis and text processing to machine translation. Lexicon acquisition, therefore, plays an essential part in getting any natural language processing system to function in the real world. Computers that process natural language require a variety of lexical information in addition to what can be found in standard dictionaries. Moreover, machine-readable dictionaries of the conventional sort have been found to be inadequate for fully supporting realistic natural language processing tasks. This volume describes corpus processing techniques that can be used to extract the additional lexical information required. Bringing together a balanced blend of the theoretical and practical, the contributions provide the most recent look at lexical acquisition techniques and practices. These include coping with unknown lexicalizations, task-driven lexical induction, categorization of lexical units, lexical semantics from corpus analysis, and measuring lexical acquisition. The problems addressed reflect a host of topics including recognition of open compounds, incremental acquisition of meanings from sentence usages, recognition of new senses of existing words, sense disambiguation, recognition of specific classes of works, and recognition and annotation of patterns of word use, each of them important to the overall language analysis process, and each employing text analysis techniques in a useful and theoretically motivated way.