Vivian Stamou


Methodological issues regarding the semi-automatic UD treebank creation of under-resourced languages: the case of Pomak
Stella Markantonatou | Nicolaos Th. Constantinides | Vivian Stamou | Vasileios Arampatzakis | Panagiotis G. Krimpas | George Pavlidis
Proceedings of the Sixth Workshop on Universal Dependencies (UDW, GURT/SyntaxFest 2023)

Pomak is an endangered oral Slavic language of Thrace/Greece. We present a short description of its interesting morphological and syntactic features in the UD framework. Because the morphological annotation of the treebank takes advantage of existing resources, it requires a different methodological approach from the one adopted for syntactic annotation that has started from scratch. It also requires the option of obtaining morphological predictions/evaluation separately from the syntactic ones with state-of-the-art NLP tools. Active annotation is applied in various settings in order to identify the best model that would facilitate the ongoing syntactic annotation.


Cleansing & expanding the HURTLEX(el) with a multidimensional categorization of offensive words
Vivian Stamou | Iakovi Alexiou | Antigone Klimi | Eleftheria Molou | Alexandra Saivanidou | Stella Markantonatou
Proceedings of the Sixth Workshop on Online Abuse and Harms (WOAH)

We present a cleansed version of the multilingual lexicon HURTLEX-(EL) comprising 737 offensive words of Modern Greek. We worked bottom-up in two annotation rounds and developed detailed guidelines by cross-classifying words on three dimensions: context, reference, and thematic domain. Our classification reveals a wider spectrum of thematic domains concerning the study of offensive language than previously thought Efthymiou et al. (2014) and reveals social and cultural aspects that are not included in the HURTLEX categories.

Morphologically annotated corpora of Pomak
Ritván Jusúf Karahóǧa | Panagiotis G. Krimpas | Vivian Stamou | Vasileios Arampatzakis | Dimitrios Karamatskos | Vasileios Sevetlidis | Nikolaos Constantinides | Nikolaos Kokkas | George Pavlidis | Stella Markantonatou
Proceedings of the Fifth Workshop on the Use of Computational Methods in the Study of Endangered Languages

The project XXXX is developing a platform to enable researchers of living languages to easily create and make available state-of-the-art spoken and textual annotated resources. As a case study we use Greek and Pomak, the latter being an endangered oral Slavic language of the Balkans (including Thrace/Greece). The linguistic documentation of Pomak is an ongoing work by an interdisciplinary team in close cooperation with the Pomak community of Greece. We describe our experience in the development of a Latin-based orthography and morphologically annotated text corpora of Pomak with state-of-the-art NLP technology. These resources will be made openly available on the XXXX site and the gold annotated corpora of Pomak will be made available on the Universal Dependencies treebank repository.


VMWE discovery: a comparative analysis between Literature and Twitter Corpora
Vivian Stamou | Artemis Xylogianni | Marilena Malli | Penny Takorou | Stella Markantonatou
Proceedings of the Joint Workshop on Multiword Expressions and Electronic Lexicons

We evaluate manually five lexical association measurements as regards the discovery of Modern Greek verb multiword expressions with two or more lexicalised components usingmwetoolkit3 (Ramisch et al., 2010). We use Twitter corpora and compare our findings with previous work on fiction corpora. The results of LL, MLE and T-score were found to overlap significantly in both the fiction and the Twitter corpora, while the results of PMI and Dice do not.We find that MWEs with two lexicalised components are more frequent in Twitter than in fiction corpora and that lean syntactic patterns help retrieve them more efficiently than richer ones.Our work (i) supports the enrichment of the lexicographical database for Modern Greek MWEs’ IDION’ (Markantonatou et al., 2019) and (ii) highlights aspects of the usage of five association measurements on specific text genres for best MWE discovery results.