INFERRING QUANTITATIVE TYPOLOGICAL TRENDS FROM MULTILINGUAL TREEBANKS. A CASE STUDY

In the past decades, linguistic typology went through a renewing phase that involved a significant change in the research questions and methods of the discipline, which is now interested in fine-grained features underlying language diversity. In this paper, we propose a novel approach to address the newly defined needs of linguistic typology by extracting qualitative and quantitative information about a wide range of features from multilingual annotated corpora based on Natural Language Processing methods and techniques. We tested our method in a case study focusing on word order variation in two widely investigated constructions, VERB-SUBJ(ect) and NOUN-ADJ(ective), with a specific view to structural and functional factors underlying the preference for one or the other order, both intra- and cross-linguistically, and their interaction. Preliminary experiments have been carried out aimed at acquiring typological evidence from a selection of linguistically annotated treebanks for three different languages, namely Italian, Spanish and English. Our results show the effectiveness of the method in letting similarities and differences also emerge from typologically close languages.