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AN HISTORICAL LINGUISTICS CORPUS (Centuries XVI-XIX)
December 2012
banza2012a
In this paper we present an evolutionary approach to the part-of-speech tagging problem. The goal of part-of- speech tagging is to assign to each word of a text its part-of-speech. The task is not straightforward, because a large percentage of words has more than one possible part-of-speech, and the right choice is determined by the surrounding word’s part-of-speeches. This means that to solve this problem we need a method to disambiguate a word’s possible tags set. Traditionally there are two groups of methods used to tackle this task. The first group is based on statistical data concerning the different context’s possibilities for a word, while the second group is based on rules, normally designed by human experts, that capture the language properties. In this work we present a solution that tries to incorporate both these approaches.
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Ana Paula Banza, Irene Rodrigues, José Saias, Filomena Gonçalves
proceedings of the International Conference on Historical Corpora 2012
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Organised by LOEWE Priority Program
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Ana Paula Banza and Irene Rodrigues and José Saias and Filomena Gonçalves, AN HISTORICAL LINGUISTICS CORPUS (Centuries XVI-XIX), , proceedings of the International Conference on Historical Corpora 2012, Organised by LOEWE Priority Program, December 2012.
Ana Paula Banza, <a href="/people/members/view.php?code=032b48c4371cf1d1523215c3f02c42de" class="author">Irene Rodrigues</a>, José Saias and Filomena Gonçalves, <b>AN HISTORICAL LINGUISTICS CORPUS (Centuries XVI-XIX)</b>, <u>proceedings of the International Conference on Historical Corpora 2012</u>, Organised by LOEWE Priority Program, December 2012.
@inproceedings {banza2012a, author = {Ana Paula Banza and Irene Rodrigues and Jos{\'e} Saias and Filomena Gon\c{c}alves}, title = {AN HISTORICAL LINGUISTICS CORPUS (Centuries XVI-XIX)}, booktitle = {proceedings of the International Conference on Historical Corpora 2012}, publisher = {Organised by LOEWE Priority Program}, abstract = {In this paper we present an evolutionary approach to the part-of-speech tagging problem. The goal of part-of- speech tagging is to assign to each word of a text its part-of-speech. The task is not straightforward, because a large percentage of words has more than one possible part-of-speech, and the right choice is determined by the surrounding word’s part-of-speeches. This means that to solve this problem we need a method to disambiguate a word’s possible tags set. Traditionally there are two groups of methods used to tackle this task. The first group is based on statistical data concerning the different context’s possibilities for a word, while the second group is based on rules, normally designed by human experts, that capture the language properties. In this work we present a solution that tries to incorporate both these approaches.}, month = {December}, year = {2012}, }
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