Abstract
Semantic Role Labeling (SRL) is a Natural Language Processing task that enables the detection of events described in sentences and the participants of these events. For Brazilian Portuguese (BP), there are two studies recently concluded that perform SRL in journalistic texts. [1] obtained F1-measure scores of 79.6, using the PropBank.Br corpus, which has syntactic trees manually revised; [8], without using a treebank for training, obtained F1-measure scores of 68.0 for the same corpus. However, the use of manually revised syntactic trees for this task does not represent a real scenario of application. The goal of this paper is to evaluate the performance of SRL on revised and non-revised syntactic trees using a larger and balanced corpus of BP journalistic texts. First, we have shown that [1]’s system also performs better than [8]’s system on the larger corpus. Second, the SRL system trained on non-revised syntactic trees performs better over non-revised trees than a system trained on gold-standard data.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
- 3.
- 4.
- 5.
Available at http://143.107.183.175:12680/verbobrasil/.
References
Alva-Manchego, F.E., Rosa, J.L.G.: Semantic role labeling for Brazilian Portuguese: a benchmark. In: Pavón, J., Duque-Méndez, N.D., Fuentes-Fernández, R. (eds.) IBERAMIA 2012. LNCS, vol. 7637, pp. 481–490. Springer, Heidelberg (2012)
Bick, E.: The Parsing System “Palavras": Automatic Grammatical Analysis of Portuguese in a Constraint Grammar Framework. Aarhus University Press, Aarhus (2000)
Bruckschen, M., Muniz, F., Souza, J., Fuchs, J., Infante, K., Muniz, M., Gonçalves, P., Vieira, R., Aluísio, S.: Anotação Lingüística em XML do Corpus PLN-BR. NILC-TR-09-08. Technical report, University of São Paulo, Brazil (2008)
Burchardt, A., Erk, K., Frank, A., Kowalski, A., Pado, S.: SALTO - a versatile multi-level annotation tool. In: Proceedings of the 5th International Conference on Language Resources and Evaluation (LREC-2006), pp. 517–520 (2006)
Carletta, J.: Assessing agreement on classification tasks: the kappa statistic. Comput. Linguist. 22(2), 249–254 (1996)
Duran, M.S., Aluísio, S.M.: Propbank-Br: a Brazilian treebank annotated with semantic role labels. In: Proceedings of the International Conference on Language Resources and Evaluation (LREC-2012), pp. 1862–1867 (2012)
Duran, M.S., Sepúlveda-Torres, L., Viviani, M.C., Hartmann, N.S., Aluísio, S.M.: Seleção de sentenças do córpus PLN-Br para compor o córpus de anotação de papéis semânticos Propbank-Br.v2. NILC-TR-14-07. Technical report, University of São Paulo, Brazil (2014)
Fonseca, E.R., Rosa, J.L.G.: A two-step convolutional neural network approach for semantic role labeling. In: Neural Networks (IJCNN), The 2013 International Joint Conference on Neural Networks, pp. 1–7 (2013)
Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics 33(1), 159–174 (1977)
Palmer, M., Gildea, D., Kingsbury, P.: The proposition bank: an annotated corpus of semantic roles. Comput. Linguist. 31(1), 71–106 (2005)
Palmer, M., Gildea, D., Xue, N.: Semantic Role Labeling, Synthesis Lectures on Human Language Technologies, vol. 3. Morgan & Claypool Publishers (2010)
Toutanova, K., Haghighi, A., Manning, C.D.: A global joint model for semantic role labeling. Comput. Linguist. 34(2), 161–191 (2008)
Acknowledgments
Part of the research developed for this work was sponsored by Samsung Eletrônica da Amazônia Ltda. under the terms of Brazilian federal law number 8.248/91. Part of the results presented in this paper were obtained through research activity in the project titled “Semantic Processing of Brazilian Portuguese Texts”, sponsored by Samsung Eletrônica da Amazônia Ltda. under the terms of Brazilian federal law number 8.248/91.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Hartmann, N.S., Duran, M.S., Aluísio, S.M. (2016). Automatic Semantic Role Labeling on Non-revised Syntactic Trees of Journalistic Texts. In: Silva, J., Ribeiro, R., Quaresma, P., Adami, A., Branco, A. (eds) Computational Processing of the Portuguese Language. PROPOR 2016. Lecture Notes in Computer Science(), vol 9727. Springer, Cham. https://doi.org/10.1007/978-3-319-41552-9_20
Download citation
DOI: https://doi.org/10.1007/978-3-319-41552-9_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-41551-2
Online ISBN: 978-3-319-41552-9
eBook Packages: Computer ScienceComputer Science (R0)