Embeddings from word2vec model described in "From Diachronic to Contextual Lexical Semantic Change: Introducing Semantic Difference Keywords (SDKs) for Discourse Studies". Full reference TBC.
Language acquisition is one of the currently much discussed topics in the field of psycholinguistics. Considerable space for future research can be seen in the development of vocabulary in Czech-speaking children. In our case, we are mainly interested in the meaning, i.e. the content of acquired words (concepts), and the role of so-called semantic features in mental representation.
The intended goal of our research is to bring new information from the above-mentioned area, to confirm or disprove some existing theoretical statements and to compare the results of foreign research with data obtained using the Czech language material. Similar research has been conducted in various world languages, but so far there are not many papers that address the issue in the Czech language environment. As part of our work, a comprehensive database of semantic features for selected concepts has been prepared. This database has been statistically processed and subsequently the data has been analyzed and interpreted on the basis of theories about the development of the child's speech competence. This material, obtained from children aged 8-9 (lower primary school) growing up in a Czech language environment, has been used in the next phase of research, in which an experiment with subjects belonging to the same age category has been performed: in a semantic task based on the phenomenon called semantic priming, the effect of featural similarity of two concepts on decision in a speeded task has been observed.
The results of the research expand the range of information published so far in this scientific field in the Czech environment. This research can provide valuable insights into children's language acquisition issues. The data gathered can also be practically beneficial not only for teachers, psychologists and speech therapists, but also for parents, for example.
Supplementary files for a comparative study of word-formation without the addition of derivational affixes (conversion) in English and Czech.
The two .csv files contain 300 verb-noun conversion pairs in English and 300 verb-noun conversion pairs in Czech, i.e. pairs where either the noun is created from the verb or the verb is created from the noun without the use of derivational affixes. In English, the noun and verb in the conversion pair have the same form. In Czech, the noun and verb in the conversion pair differ in inflectional affixes.
The pairs are supplied with manual semantic annotation based on cognitive event schemata.
A file with the Appendix includes a list of dictionary definition phrases used as a basis for the semantic annotation.
Diachronic Corpus of Early Written Latvian Texts (16-18th c.). > 1 mill. running words (work is on-going). The main data are ecclesiastical texts, secular texts (laws, fiction) and some first bilingual (Latvian-German) dictionaries. A KWIC-based concordancer, as well as inverse vocabulary, frequency lists and word lists are provided. Some source facsimiles are available.
Sentiment analysis models for Czech language. Models are three Czech sentiment analysis datasets(http://liks.fav.zcu.cz/sentiment/): Mall, CSFD, Facebook, and joint data from all three datasets above, using Czech version of BERT model, RobeCzech.
We present the best model for every dataset. Mall and CSFD models are new state-of-the-art for respective data.
Demo jupyter notebook is available on the project GitHub.
These models are a part of Czech NLP with Contextualized Embeddings master thesis.
Semantic net `sholva' contains more than 150 000 records for which there was sufficient agreement among annotators. Indvidual words are labeled in the following categories:
person, person / individual, event and substance.