RESUMO Este artigo descreve a metodologia para a integração de predicados nominais, do tipo construções com verbo-suporte (CVS), no analisador sintático automático XIP, que é utilizado pela cadeia de processamento do Português STRING. Trata-se, mais especificamente, de 580 CVS com o verbo dar e um nome predicativo, cujas propriedades sintático-semânticas foram descritas, formalizadas e, em seguida, integradas à gramática do XIP, por meio de regras, a fim de extrair a dependência SUPPORT entre o nome predicativo (Npred) e o verbo-suporte (Vsup). A necessidade de tratar automaticamente as CVS decorre do fato de que elas são diferentes de construções com verbo pleno, possuem estruturas sintáticas complexas, possuem propriedades sintático-semânticas específicas e admitem transformações sintáticas sistemáticas, ainda que lexicalmente determinadas. O conceito de CVS, bem como a abordagem léxico-sintática adotada, segue os princípios teóricos e metodológicos do Léxico-Gramática. Como resultado da integração desses dados ao parser XIP, o sistema atingiu precisão de 85%, abrangência de 87%, acurácia de 80% e medida-F de 86%.

ABSTRACT This article describes the methodology for the integration of nominal predicates, that is, support verb constructions (SVC), in the XIP parser, which is used by STRING, a Portuguese processing chain. More specifically, 580 SVC with the support verb (Vsup) dar ‘give’ and a predicative noun (Npred), whose syntactic-semantic properties have been described, formalized and then integrated into the Portuguese grammar of XIP, by means of rules, in order to extract the syntactic dependency (noted SUPPORT) between the Npred and the Vsup. The need to automatically treat SVC derives from the fact that they are different from full-verb constructions, have complex syntactic structures, have specific syntactic-semantic properties, and allow several systematic, albeit lexically determined, syntactic transformations. The concept of SVC, as well as the lexical-syntactic approach here adopted, follows the theoretical and methodological principles of the Lexicon-Grammar theory. As a result of integrating these data into the XIP parser, the system achieved 85% precision, 87% recall, 80% accuracy and 86% F-measure on an evaluation corpus, specifically built for this purpose.

Abstract. In this article, we improve the extraction of semantic relations between textual elements as it is currently performed by STRING, a hybrid statistical and rule-based Natural Language Processing (NLP) chain for Portuguese, by targeting whole-part relation (meronymy), that is, a semantic relation between two entities of which one is perceived as a constituent part of the other, or between a set and its member. In this case, we focus on the type of meronymy involving human entities and body-part nouns (Nbp) (e.g., O Pedro partiu uma perna 'Pedro broke a leg': WHOLE-PART (Pedro, perna) WHOLE-PART (Pedro, leg) '). In orderto extract this type of whole-part relations, a rule-based meronymy extraction module has been built and integrated in the grammar of the STRING system. The module was evaluated with promising results.