Eligibility of English Hypernymy Resources for Extracting Knowledge from Natural-Language Texts

Author:

Sychev Oleg,Kamennov Yaroslav

Publisher

Springer International Publishing

Reference14 articles.

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2. Bertoldi, A., de Oliveira Chishman, R.L.: Developing a frame-based lexicon for the Brazilian legal language: the case of the criminal$$\_$$process frame. In: Palmirani, M., Pagallo, U., Casanovas, P., Sartor, G. (eds.) AI Approaches to the Complexity of Legal Systems. Models and Ethical Challenges for Legal Systems, Legal Language and Legal Ontologies, Argumentation and Software Agents, pp. 256–270. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-35731-2_18

3. Chiu, J.P., Nichols, E.: Named entity recognition with bidirectional LSTM-CNNs. Trans. Assoc. Comput. Linguist. 4, 357–370 (2016). https://doi.org/10.1162/tacl_a_00104. https://www.aclweb.org/anthology/Q16-1026

4. Deschacht, K., Moens, M.F.: Efficient hierarchical entity classifier using conditional random fields. In: Proceedings of the 2nd Workshop on Ontology Learning and Population: Bridging the Gap between Text and Knowledge, Sydney, Australia, pp. 33–40. Association for Computational Linguistics, July 2006. https://www.aclweb.org/anthology/W06-0505

5. Gangemi, A., Navigli, R., Velardi, P.: The OntoWordNet project: extension and axiomatization of conceptual relations in WordNet. In: Meersman, R., Tari, Z., Schmidt, D.C. (eds.) On The Move to Meaningful Internet Systems 2003: CoopIS, DOA, and ODBASE, pp. 820–838. Springer, Heidelberg (2003)

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