Exploring Semantic Information in Hindi WordNet for Hindi Dependency Parsing
Sambhav Jain, Naman Jain, Aniruddha Tammewar, Riyaz Ahmad Bhat, Dipti Misra Sharma · 2013
In this paper, we present our efforts to-wards incorporating external knowledge from Hindi WordNet to aid dependency parsing. We conduct parsing experiments on Hindi, an Indo-Aryan language, utiliz-ing the information from concept ontolo-gies available in Hindi WordNet to com-plement the morpho-syntactic information already available. The work is driven by the insight that concept ontologies cap-ture a specific real world aspect of lexical items, which is quite distinct and unlikely to be deduced from morpho-syntactic in-formation such as morph, POS-tag and chunk. This complementing information is encoded as an additional feature for data driven parsing and experiments are con-ducted. We performed experiments over datasets of different sizes. We achieved an improvement of 1.1 % (LAS) when train-ing with 1,000 sentences and 0.2 % (LAS) with 13,371 sentences over the baseline. The improvements are statistically signifi-cant at p<0.01. The higher improvements on 1,000 sentences suggest that the se-mantic information could address the data sparsity problem. 1