References
- 1Akbik, A., Blythe, D., & Vollgraf, R. (2018). Contextual string embeddings for sequence labeling. Proceedings of the 27th International Conference on Computational Linguistics, Santa Fé, USA.
- 2Baron, A., & Rayson, P. (2008). VARD2: A tool for dealing with spelling variation in historical corpora. Postgraduate Conference in Corpus Linguistics, Birmingham, U.K.
- 3Birch, C., Oom S., & Beecham, J. (2007). Rectangular and hexagonal grids used for observation, experiment and simulation in ecology. Ecological Modelling, 206(3–4), 347–359. DOI: 10.1016/j.ecolmodel.2007.03.041
- 4Bojanowski, P., Grave, E., Joulin, A., & Mikolov, T. (2017). Enriching word vectors with subword information. Transactions of the Association for Computational Linguistics, 5, 135–146. DOI: 10.1162/tacl_a_00051
- 5Cameron, H. F., Gonçalves, M. F., & Quaresma, P. (2020). Linguistic and orthographical classic Portuguese variants challenges for NLP. Proceedings of the 14th International Conference on the Computational Processing of Portuguese, Évora, Portugal.
- 6Chiu, J. P., & Nichols, E. (2016). Named entity recognition with bidirectional LSTM-CNNS. Transactions of the Association for Computational Linguistics, 4, 357–370. DOI: 10.1162/tacl_a_00104
- 7Chorão, M. J. M. B. (1987). Inquéritos promovidos pela Coroa no século XVIII. Revista de História Económica e Social, 1a série, 21, 93–130.
- 8Christaller, W., & Baskin, C. W. (1966). Central places in southern Germany. Engelwood Cliffs, NJ: Prentice-Hall.
- 9Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., & Kuksa, P. (2011). Natural language processing (almost) from scratch. Journal of Machine Learning Research, 12, 2493–2537. Aug.
- 10Consoli, B. S., Santos, J., Gomes, D., Cordeiro, F., Vieira, R., & Moreira, V. (2020). Embeddings for named entity recognition in geoscience Portuguese literature. Proceedings of the 12th Language Resources and Evaluation Conference, Marseílle, France.
- 11Costa, A. C. (1706–1712). Corografia Portugueza e descripçam topografica do famoso reyno de Portugal: com as noticias das fundações das cidades, villas, & lugares, que contem, varões illustres, genealogias das familias nobres, fundações de conventos, catalogos dos bispos, antiguidades, maravilhas de natureza, edificios & outras curiosas observaçoens, Tomo primeyro[-terceyro], vol. 1-2-3. Lisboa: na officina de Valentim da Costa Deslandes.
- 12dos Dereza, O. (2018).
Lemmatization for ancient languages: Rules or neural networks? In D. Ustalov, A. Filchenkov, L. Pivovarova & J. Žižka (Eds.), Artificial Intelligence and Natural Language. AINL 2018. Communications in Computer and Information Science, vol 930. Springer. DOI: 10.1007/978-3-030-01204-5_4 - 13Santos, C. N., & Guimarães, V. (2015). Boosting named entity recognition with neural character embeddings. Proceedings of the 5th Named entity workshop, Beijin, China. DOI: 10.18653/v1/W15-3904
- 14Gonçalves, M. F. (2003). As ideias ortográficas em Portugal: de Madureira Feijó a Gonçalves Viana (1734–1911). Lisboa: Fundação Calouste Gulbenkian.
- 15Hubková, H., Kral, P., & Pettersson, E. (2020). Czech historical named entity corpus v 1.0. Proceedings of the 12th Language Resources and Evaluation Conference, Marseille: France.
- 16Jurafsky, D., & Martin, J. H. (2000). Speech and language processing: An introduction to natural language processing, computational linguistics, and speech recognition (3rd ed. draft). Stanford University.
- 17Kemmler, R. (2001). Para uma história da ortografia portuguesa: o texto metaortográfico e a sua periodização do século xvi até a reforma ortográfica de 1911. Lusorama. Zeitschrift für Lusitanistik. Revista de Estudos sobre os Países de Língua Portuguesa, 47–48, 128–319.
- 18Klie, J.-C., Bugert, M., Boullosa, B., de Castilho, R. E., & Gurevych, I. (2018). The inception platform: Machine-assisted and knowledge-oriented interactive annotation. Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, Santa Fé, USA.
- 19Lample, G., Ballesteros, M., Subramanian, S., Kawakami, K., & Dyer, C. (2016). Neural architectures for named entity recognition. arXiv preprint arXiv:1603.01360.
- 20Mateus, M. H. M., & Cardeira, E. (2007). Norma e variação. Alfragide: Editorial Caminho.
- 21McHugh, M. L. (2012). Interrater reliability: The kappa statistic. Biochemia medica, 22(3), 276–282. DOI: 10.11613/BM.2012.031
- 22Nothman, J., Ringland, N., Radford, W., Murphy, T., & Curran, J. R. (2013). Learning multilingual named entity recognition from Wikipedia. Artificial Intelligence, 194, 151–175. DOI: 10.1016/j.artint.2012.03.006
- 23Ortiz Suárez, P. J., Romary, L., & Sagot, B. (2020). A monolingual approach to contextualised word embeddings for mid-resource languages. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. DOI: 10.18653/v1/2020.acl-main.156
- 24Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., & Duchesnay, É. (2011). Scikit-learn: Machine learning in python. Journal of Machine Learning Research, 12(85), 2825–2830.
- 25Romão, R. M. A. (2019). Os lugares centrais em Portugal: a área de influência de Coimbra. Masters Thesis, Instituto Superior de Economia e Gestão.
- 26Romein, C. A., Kemman, M., Birkholz, J. M., Baker, J., DeGruijter, M., Meroño-Peñuela, A., Ries, T., Ros, R., & Scagliola, S. (2020). State of the field: digital history. History, 105(365), 291–312. DOI: 10.1111/1468-229X.12969
- 27Sang, T. K., & Erik, F. (2002). Introduction to the CoNLL-2002 shared task: language-independent named entity recognition. Proceedings of CoNLL-2002, Conference on Natural Language Learning, Taipei, Taiwan.
- 28Santos, J. A. (1995). As freguesias: História e actualidade. Oeiras: Celta.
- 29Santos, D., & Cardoso, N. (2007). Reconhecimento de entidades mencionadas em português: Documentação e actas do HAREM, a primeira avaliação conjunta na área. Retrieved from
https://www.linguateca.pt/aval_conjunta/LivroHAREM/Livro-SantosCardoso2007.pdf - 30Santos, J., Consoli, B., dos Santos, C., Terra, J., Collonini, S., & Vieira, R. (2019a). Assessing the impact of contextual embeddings for Portuguese named entity recognition. Proceedings of the 8th Brazilian Conference on Intelligent Systems. Salvador, Brasil.
- 31Santos, J., dos Santos, H. D. P., & Vieira, R. (2020b). Fall detection in clinical notes using language models and token classifier. Proceedings of the 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020, Rochester, USA.
- 32Santos, I., Olival, F., & Sequeira, O. (2020a). Excavating the data pit: the Portuguese parish memories (1758) as a gold standard. DHandNLP@PROPOR, Workshop on Digital Humanities and Natural Language Processing, Évora, Portugal.
- 33Santos, J., Terra, J., Consoli, B. S., & Vieira, R. (2019b). Multidomain contextual embeddings for named entity recognition. Proceedings of the 35th Conference of the Spanish society for natural language processing, Bilbao, Spain.
- 34Schmitt, X., Kubler, S., Robert, J., Papadakis, M., & Le-Traon, Y. (2019). A replicable comparison study of NER software: Stanford NLP, NLTK, Open NLP, Spacy, Gate. Sixth International Conference on Social Networks Analysis, Management and Security, Granada, Sapin.
- 35Souza, F., Nogueira R., & Lotufo, R. (2019). Portuguese named entity recognition using BERT-CRF. arXiv preprint arXiv:1909.10649.
- 36Verdelho, T. (1987). Latinização na história da Língua Portuguesa – o testemunho dos dicionários. Arquivos do Centro Cultural Português (volume de homenagem a Paul Teyssier), XXIII, 157–187.
