Maria Kobozeva

Federal Research Center 'Compurer Science and Control' of Russian Academy of Sciences · Institute for Systems Analysis of Russian Academy of Sciences

This work presents the first fully-fledged discourse parser for Russian based on the Rhetorical Structure Theory of Mann and Thompson (1988). For the segmentation, discourse tree construction, and discourse relation classification we employ deep learning models. With the help of multiple word embedding techniques, the new state of the art for disco...

The paper presents a corpus study of the discourse features in the corpus of blogs. It is based on the data of Ru-RSTreebank annotated within the framework of the Rhetorical Structure theory [Mann, Thompson 1988]. The Ru-RSTreebank represents genres of news and popular science, scientific papers, and blogs texts. Blog subcorpus contains such topics...

Study of cause-effect discourse connectives can help in automated discourse processing and automatic identification of argument units. Besides conjunctions and other functional words and expressions, there are different multi-word expressions containing content-words (e.g. is etogo sleduet ‘it follows that’) that have the function of cause-effect c...

The paper deals with the pilot version of the first RST discourse treebank for Russian. The project started in 2016. At present, the treebank consists of sixty news texts annotated for rhetorical relations according to RST scheme. However, this scheme was slightly modified in order to achieve higher inter-annotator agreement score. During the annot...

For many natural language processing tasks (machine translation evaluation, anaphora resolution, information retrieval, etc.) a corpus of texts annotated for discourse structure is essential. As for now, there are no such corpora of written Russian, which stands in the way of developing a range of applications. This paper presents the first steps o...

This paper presents an adaptation of the Rhetorical Structure Theory to the Russian language and the development of an RST-corpus that will be used for training of an automatic discourse parser in the future. Authors’ survey shows that discourse analysis improves performance of systems for machine translation, automatic summarization, author identi...