Linguistically Rich Graph Based Data Driven Parsing For Hindi
Samar Husain, Raghu Pujitha Gade, Rajeev Sangal · 2011
In this paper we show how linguistic knowledge can be incorporated during graph based parsing. We use MSTParser and show that the use of a constraint graph, instead of a complete graph, to extract a spanning tree improves parsing accuracy. A constraint graph is formed by using linguistic knowledge of a constraint based parsing system. Through a series of experiments we formulate the optimal constraint graph that gives us the best accuracy. These experiments show that some of the previous MSTParser errors can be corrected consistently. It also shows the limitations of the proposed approach.