Abstract
In this paper, we describe a tool kit for natural language analysis, the MSLR parser tool kit.The ‘MSLR parser’ is based on the generalized LR parsing algorithm, and integrates morphological and syntactic analysis of unsegmented sentences. The'LR table generator'constructs an LR table from a context free grammar and a connection matrix describing adjacency constraints between part-of-speech pairs. By incorporating connection matrix-based constraints into the LR table, it is possible to both reject any locally implausible parsing results, and reduce the size of the LR table. Then, using the generated LR table and a lexicon, the MSLR parser outputs parse trees based on morphological and syntactic analysis of input sentences. In addition to this, the MSLR parser accepts sentence inputs including partial syntactic constraints denoted by pairs of brackets, and suppresses the generation of any parse trees not satisfying those constraints. Furthermore, it can be trained according to the probabilistic generalized LR (PGLR) model, which is a mildly context sensitive language model. It can also rank parse trees in order of the overall probability returned by the trained PGLR model.
