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    Zhang, G. and Nulty, Paul and Lillis, D. (2022) Enhancing legal argument mining with domain pre-training and neural networks. Journal of Data Mining & Digital Humanities NLP4DH , ISSN 2416-5999.

    Book Section

    Nulty, Paul (2023) Operationalising conceptual structure. In: de Bolla, P. (ed.) Explorations in the Digital History of Ideas - New Methods and Computational Approaches Search within full text. Cambridge University Press, pp. 54-76. ISBN 9781009263610.

    Zhang, G. and Nulty, Paul and Lillis, D. (2023) Argument mining with graph representation learning. In: UNSPECIFIED (ed.) Proceedings of the Nineteenth International Conference on Artificial Intelligence and Law. ACM Digital LIbrary, pp. 371-380. ISBN 9798400701979.

    Zhang, G. and Nulty, Paul and Lillis, D. (2022) A decade of legal argumentation mining: datasets and approaches. In: Rosso, P. and Basile, V. and Martínez, R. and Métais, E. and Meziane, F. (eds.) Natural Language Processing and Information Systems - 27th International Conference on Applications of Natural Language to Information Systems, NLDB 2022, Valencia, Spain, June 15–17, 2022, Proceedings. Lecture Notes in Computer Science 13286. Springer, pp. 240-252. ISBN 9783031084720.

    Nulty, Paul (2007) Semantic classification of noun phrases using web counts and learning algorithms. In: Carroll, J.A. and van den Bosch, A. and Zaenen, A. (eds.) Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics: ACL 2007. The Association for Computational Linguistics, pp. 79-84.

    Nulty, Paul and Marquez i Villodre, l. and Wicentowski, R. (2007) UCD-PN: classification of semantic relations between nominals using wordnet and web counts. In: Agirre, E. (ed.) Proceedings of the 4th International Workshop on Semantic Evaluations: SemEval@ACL 2007. The Association for Computer Linguistics, pp. 374-377.

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