Mihaela Cristescu


A Romanian Treebank Annotated with Verbal Multiword Expressions
Verginica Barbu Mititelu | Mihaela Cristescu | Maria Mitrofan | Bianca-Mădălina Zgreabăn | Elena-Andreea Bărbulescu
Proceedings of the 5th International Conference on Computational Linguistics in Bulgaria (CLIB 2022)

In this paper we present a new version of the Romanian journalistic treebank annotated with verbal multiword expressions of four types: idioms, light verb constructions, reflexive verbs and inherently adpositional verbs, the last type being recently added to the corpus. These types have been defined and characterized in a multilingual setting (the PARSEME guidelines for annotating verbal multiword expressions). We present the annotation methodologies and offer quantitative data about the expressions occurring in the corpus. We discuss the characteristics of these expressions, with special reference to the difficulties they raise for the automatic processing of Romanian text, as well as for human usage. Special attention is paid to the challenges in the annotation of the inherently adpositional verbs. The corpus is freely available in two formats (CUPT and RDF), as well as queryable using a SPARQL endpoint.


The Romanian Corpus Annotated with Verbal Multiword Expressions
Verginica Barbu Mititelu | Mihaela Cristescu | Mihaela Onofrei
Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019)

This paper reports on the Romanian journalistic corpus annotated with verbal multiword expressions following the PARSEME guidelines. The corpus is sentence split, tokenized, part-of-speech tagged, lemmatized, syntactically annotated and verbal multiword expressions are identified and classified. It offers insights into the frequency of such Romanian word combinations and allows for their characterization. We offer data about the types of verbal multiword expressions in the corpus and some of their characteristics, such as internal structure, diversity in the corpus, average length, productivity of the verbs. This is a language resource that is important per se, as well as for the task of automatic multiword expressions identification, which can be further used in other systems. It was already used as training and test material in the shared tasks for the automatic identification of verbal multiword expressions organized by PARSEME.