This paper presents a supervised semantic role labeler for Hindi which can be extended to Urdu as well. We propose a set of new features enriching the existing baseline system for these languages. We break the system into two subsequent tasks - Argument Identification and Argument Classification respectively. Our experiments show a reasonable improvement with respect to the current baseline for Hindi, mainly for the classification step. We also report significant improvements for Argument Identification task in Urdu. Finally, we create a new baseline for the Hindi using 5-fold cross-validation and we capture results excluding the null class and including the null class exclusively. We also extend the same work on Urdu and report the results.
@InProceedings{GUPTA18.28, author = {Aishwary Gupta and Manish Shrivastava}, title = {Enhancing Semantic Role Labeling in Hindi and Urdu}, booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {may}, date = {7-12}, location = {Miyazaki, Japan}, editor = {Kiyoaki Shirai}, publisher = {European Language Resources Association (ELRA)}, address = {Paris, France}, isbn = {979-10-95546-24-5}, language = {english} }
Summary of the paper