Abstract
In this work, we apply and evaluate a machine-learning-based system to Portuguese clause identification. To the best of our knowledge, this is the first machine-learning-based approach to this task. The proposed system is based on Entropy Guided Transformation Learning. In order to train and evaluate the proposed system, we derive a clause annotated corpus from the Bosque corpus of the Floresta Sintá(c)tica Project – an European and Brazilian Portuguese treebank. We include part-of-speech (POS) tags to the derived corpus by using an automatic state-of-the-art tagger. Additionally, we use a simple heuristic to derive a phrase-chunk-like (PCL) feature from phrases in the Bosque corpus. We train an extractor to this sub-task and use it to automatically include the PCL feature in the derived clause corpus. We use POS and PCL tags as input features in the proposed clause identifier. This system achieves a F β= 1 of 73.90, when using the golden values of the PCL feature. When the automatic values are used, the system obtains F β= 1= 69.31. These are promising results for a first machine learning approach to Portuguese clause identification. Moreover, these results are achieved using a very simple PCL feature, which is generated by a PCL extractor developed with very little modeling effort.
This work was partially funded by CNPq and FAPERJ grants 557.128/2009-9 and E-26/170028/2008. The first author was supported by a CNPq doctoral fellowship.
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
Preview
Unable to display preview. Download preview PDF.
References
Sang, E.F.T.K., Déjean, H.: Introduction to the CoNLL 2001 shared task: Clause identification. In: Proceedings of Fifth Conference on Computational Natural Language Learning, Toulouse, France (2001)
Milidiú, R.L., dos Santos, C.N., Duarte, J.C.: Phrase chunking using entropy guided transformation learning. In: Proceedings of ACL 2008: HLT, pp. 647–655. Association for Computational Linguistics, Columbus (2008)
Bick, E.: The Parsing System Palavras: Automatic Grammatical Analysis of Portuguese in a Constraint Grammar Framework. PhD thesis, Aarhus University, Aarhus, Denmark. Aarhus University Press (November 2000)
Leffa, V.J.: Clause processing in complex sentences. In: Proceedings of the First International Conference on Language Resources and Evaluation, Granada, Espanha, vol. 2, pp. 937–943 (1998)
Carreras, X., Màrquez, L.: Boosting trees for clause splitting. In: Proceedings of Fifth Conference on Computational Natural Language Learning, Toulouse, France (2001)
Fernandes, E.R., Pires, B.A., dos Santos, C.N., Milidiú, R.L.: Clause identification using entropy guided transformation learning. In: Proceedings of the 7th Brazilian Symposium in Information and Human Language Technology (STIL 2009), São Carlos, Brazil (2009)
Carreras, X., Màrquez, L., Castro, J.: Filtering-ranking perceptron learning for partial parsing. Machine Learning 60(1–3), 41–71 (2005)
dos Santos, C.N., Milidiú, R.L.: Entropy Guided Transformation Learning. In: Foundations of Computational Intelligence, vol. 1 of Learning and Approximation. vol. 201 of Studies in Computational Intelligence, pp. 159–184. Springer, Heidelberg (2009)
Brill, E.: Transformation-based error-driven learning and natural language processing: a case study in part-of-speech tagging. Computational Linguistics 21(4), 543–565 (1995)
Freitas, C., Rocha, P., Bick, E.: Floresta Sintá(c)tica: Bigger, thicker and easier. In: Teixeira, A., de Lima, V.L.S., de Oliveira, L.C., Quaresma, P. (eds.) PROPOR 2008. LNCS (LNAI), vol. 5190, pp. 216–219. Springer, Heidelberg (2008)
dos Santos, C.N., Milidiú, R.L., Renteria, R.P.: Portuguese part-of-speech tagging using entropy guided transformation learning. In: Teixeira, A., de Lima, V.L.S., de Oliveira, L.C., Quaresma, P. (eds.) PROPOR 2008. LNCS (LNAI), vol. 5190, pp. 143–152. Springer, Heidelberg (2008)
Abney, S.: Parsing by Chunks. In: Principle-Based Parsing. Kluwer Academic Publishers, Dordrecht (1991)
Freitas, M.C., Garrao, M., Oliveira, C., Santos, C.N.d., Silveira, M.: A anotação de um corpus para o aprendizado supervisionado de um modelo de sn. In: Proceedings of the III TIL / XXV Congresso da SBC, São Leopoldo - RS - Brasil (2005)
Sang, E.F.T.K.: Text chunking by system combination. In: Proceedings of Conference on Computational Natural Language Learning, Lisbon, Portugal (2000)
Milidiú, R.L., dos Santos, C.N., Duarte, J.C.: Portuguese corpus-based learning using ETL. Journal of the Brazilian Computer Society 14(4) (2008)
Milidiú, R.L., dos Santos, C.N., Crestana, C.E.M.: A token classification approach to dependency parsing. In: Proceedings of the 7th Brazilian Symposium in Information and Human Language Technology (STIL 2009), São Carlos, Brazil (2009)
Fernandes, E.R., dos Santos, C.N., Milidiú, R.L.: Portuguese language processing service. In: Proceedings of the Web in Ibero-America Alternate Track of the 18th World Wide Web Conference, Madrid (2009)
Carreras, X., Màrquez, L., Punyakanok, V., Roth, D.: Learning and inference for clause identification. In: Proceedings of the Thirteenth European Conference on Machine Learning, pp. 35–47 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fernandes, E.R., dos Santos, C.N., Milidiú, R.L. (2010). A Machine Learning Approach to Portuguese Clause Identification. In: Pardo, T.A.S., Branco, A., Klautau, A., Vieira, R., de Lima, V.L.S. (eds) Computational Processing of the Portuguese Language. PROPOR 2010. Lecture Notes in Computer Science(), vol 6001. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12320-7_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-12320-7_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12319-1
Online ISBN: 978-3-642-12320-7
eBook Packages: Computer ScienceComputer Science (R0)