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.

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.

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.