NLP for D&D
PI: Nisansa de Silva
This project attempts to generate adventures, images, and encounters for Dungeons and Dragons, the world's most popular Table Top Role Playing Game.
Home ➤ Keyword ➤
Named Entity Recognition
Projects
SigmaLaw
PI: Nisansa de Silva
This project delves into the synergy between Natural Language Processing (NLP) and the legal domain, presenting novel solutions to enduring challenges.
People
Publications
Journal Papers
Chamodi Samarawickrama, Melonie de Almeida, Nisansa de Silva, Gathika Ratnayaka, and Amal Shehan Perera, "Legal Party Extraction from Legal Opinion Texts Using Recurrent Deep Neural Networks", Journal of Data Intelligence, vol. 3, no. 3, pp. 350--365, 2022. doi: 10.26421/JDI3.3-4
Conference Papers
Gayashan Weerasundara and Nisansa de Silva, "Comparative Analysis of Named Entity Recognition in the Dungeons and Dragons Domain", in Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, 2023, pp. 1225--1233.
Aravinth Sivaganeshan and Nisansa De Silva, "Fine Tuning Named Entity Extraction Models for the Fantasy Domain", in 2023 Moratuwa Engineering Research Conference (MERCon), 2023, pp. 346--351. doi: 10.1109/MERCon60487.2023.10355501
Melonie de Almeida, Chamodi Samarawickrama, Nisansa de Silva, Gathika Ratnayaka, and Shehan Perera, "Identifying Legal Party Members from Legal Opinion Documents using Natural Language Processing", in The 23rd International Conference on Information Integration and Web Intelligence, 2021, pp. 259--266. doi: 10.1145/3487664.3487700
Chamodi Samarawickrama, Melonie de Almeida, Nisansa de Silva, Gathika Ratnayaka, and Amal Shehan Perera, "Party Identification of Legal Documents using Co-reference Resolution and Named Entity Recognition", in 2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS), 2020, pp. 494--499. doi: 10.1109/ICIIS51140.2020.9342720
Melonie de Almeida, Chamodi Samarawickrama, Nisansa de Silva, Gathika Ratnayaka, and Amal Shehan Perera, "Legal Party Extraction from Legal Opinion Text with Sequence to Sequence Learning", in 2020 20th International Conference on Advances in ICT for Emerging Regions (ICTer), 2020, pp. 143--148. doi: 10.1109/ICTer51097.2020.9325488