id: 06080265
dt: a
an: 06080265
au: Ferneda, Edilson; do Prado, Hércules Antonio; Batista, Augusto Herrmann;
    Pinheiro, Marcello Sandi
ti: Extracting definitions from Brazilian legal texts.
so: Murgante, Beniamino (ed.) et al., Computational science and its
    applications ‒ ICCSA 2012. 12th international conference, Salvador de
    Bahia, Brazil, June 18‒21, 2012. Proceedings, Part III. Berlin:
    Springer (ISBN 978-3-642-31136-9/pbk). Lecture Notes in Computer
    Science 7335, 631-646 (2012).
py: 2012
pu: Berlin: Springer
la: EN
cc: 
ut: information extraction; definition extraction; natural language processing
ci: 
li: doi:10.1007/978-3-642-31137-6_48
ab: Summary: In order to avoid ambiguity and to ensure, as far as possible, a
    strict interpretation of law, legal texts usually define the specific
    lexical terms used within their discourse by means of normative rules.
    With an often large amount of rules in effect in a given domain,
    extracting these definitions manually would be a costly undertaking.
    This paper presents an approach to cope with this problem based in a
    variation of an automated technique of natural language processing of
    Brazilian Portuguese texts. For the sake of generality, the proposed
    solution was developed to address the more general problem of building
    a glossary from domain specific texts that contain definitions amongst
    their content. This solution was applied to a corpus of texts on the
    telecommunications regulations domain and the results are reported. The
    usual pipeline of natural language processing has been followed:
    preprocessing, segmentation, and part-of-speech tagging. A set of
    feature extraction functions is specified and used along with reference
    glossary information on whether or not a text fragment is a definition,
    to train a SVM classifier. At last, the definitions are extracted from
    the texts and evaluated upon a testing corpus, which also contains the
    reference glossary annotations on definitions. The results are then
    discussed in light of other definition extraction techniques.
rv: