Verblexpor : um recurso léxico com anotação de papéis semânticos para o português

(2015) 197 pages, published

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(en) This dissertation aims at developing a lexical resource of verbs annotated with semantic roles, called VerbLexPor, and based on other resources, such as VerbNet, PropBank, and FrameNet. The theoretical bases of this study lies in Corpus Linguistics and Natural Language Processing (NLP), so that it aims at contributing to both Linguistics and Computer Science. The hypotheses are: a) one set of semantic roles can be applied to different genres; and b) the differences among genres are shown by the ranking of semantic roles. The development of VerbLexPor has two corpora at the basis: a specialized one, with more than 1.6 million words, composed by scientific papers in the field of Cardiology from three Brazilian journals; and a non-specialized one, with more than 1 million words, composed by newspaper articles from Diário Gaúcho. The corpora were analyzed with the parser PALAVRAS, and sentence, verb and argument information was extracted and stored in a database. VerbLexPor has 192 verbs and more than 15 thousand arguments annotated with semantic roles, distributed among more than 6 thousand sentences. We observed that Diário Gaúcho has a more direct syntax, with less passive voice and adjuncts, while Cardiology has more passive voice and more INSTRUMENTS for subjects, and fewer AGENTS. We also conducted some parallel experiments, such as semantic role labeling with multiple annotators and automatic verbal clustering. In the multiple annotators task, each of them annotated exactly the same 25 sentences. They received an annotation manual and basic training (explanation on the task and two annotation examples). We used multi-π to evaluate agreement among annotators, and results were π = 0,25. Reasons for this low agreement may be a lack of a thoroughly developed training. The verbal clustering task showed that syntax and semantics are equally important for verbal clustering. This study contributes to Linguistics, with a verbal lexicon annotated with semantic roles, and also to Computer Science, with data that can be assessed and processed for various NLP applications, especially because the data are available in both XML and SQL formats.
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Zilio, L. (2015). Verblexpor : um recurso léxico com anotação de papéis semânticos para o português. Universidade Federal do Rio Grande do Sul. https://hdl.handle.net/2078.5/277121