In this paper we apply a set of rules to identify the root of a dependency tree, following the Universal Dependencies formalism and starting from the constituency annotation of the York-Toronto-Helsinki Parsed Corpus of Old English Prose (YCOE). This rule-based root-identification task represents the first step towards a rule-based automatic conversion of this valuable resource into the UD format. After presenting Old English and the annotated resources available for this language, we describe the different rules we applied and then we discuss the results and the errors.

This paper shows how WordNets can be employed in tandem with morpho-syntactically annotated corpora to study poetic formulas. Pairing the lexico-semantic information of the Sanskrit WordNet with morpho-syntactic annotation from the Vedic Treebank, we perform a pilot study of formulas including SPEECH verbs in the RigVeda, the most ancient text of the. Sanskrit literature.

In this paper we test the parsing performances of a multilingual parser on Old English data using different sets of languages, alone and combined with the target language, to train the models. We compare the results obtained by the models and we analyze more in deep the annotation of some peculiar syntactic constructions of the target language, providing plausible linguistic explanations of the errors made even by the best performing models.

Indo-European preverbs are uninflected morphemes attaching to verbs and modifying their meaning. In Early Vedic and Homeric Greek, these morphemes held ambiguous morphosyntactic status raising issues for syntactic annotation. This paper focuses on the annotation of preverbs in so-called “absolute” position in two Universal Dependencies treebanks. This issue is related to the broader topic of how to annotate ellipsis in Universal Dependencies. After discussing some of the current annotations, we propose a new scheme that better accounts for the variety of absolute constructions.

Many tools are available to query a dependency treebank, but they require the users to know a query language. In this paper I present UDeasy, an application whose main goal is to allow the users to easily query and extract patterns from a dependency treebank in CoNLL-U format.

Research in linguistic typology has shown that languages do not fall into the neat morphological types (synthetic vs. analytic) postulated in the 19th century. Instead, analytic and synthetic must be viewed as two poles of a continuum and languages may show a mix analytic and synthetic strategies to different degrees. Unfortunately, empirical studies that offer a more fine-grained morphological classification of languages based on these parameters remain few. In this paper, we build upon previous research by Liu & Xu (2011) and investigate the possibility of inferring information on morphological complexity from syntactic dependency networks.