This paper discusses the design principles and procedures for creating a balanced corpus for research in computational literary studies, building on the experience of computational linguistics but adapting it to the specificities of the digital humanities. It showcases the development of the Metadata-enriched Polish Novel Corpus from the 19th and 20th centuries (19/20MetaPNC), consisting of 1,000 novels from 1854–1939, as an illustrative case and proposes a comprehensive workflow for the creation and reuse of literary corpora. What sets 19/20MetaPNC apart is its approach to balance, which considers the spatial dimension, the inclusion of non-canonical texts previously overlooked by other corpora, and the use of a complex, multi-stage metadata enrichment and verification process. Emphasis is placed on research-oriented metadata design, efficient data collection and data sharing according to the FAIR principles as well as 5- and 7-star data standards to increase the visibility and reusability of the corpus. A knowledge graph-based solution for the creation of exchangeable and machine-readable metadata describing corpora has been developed. For this purpose, metadata from bibliographic catalogs and other sources were transformed into Linked Data following the bibliodata LODification approach.

The article discusses the challenges of cross-linguistic dialogue act annotation, which involves using methods developed for one language to annotate conversations in another language. The article specifically focuses on the research on dialogue act annotation in Polish, based on the ISO standard developed for English. The article examines the differences between Polish and English in dialogue act annotation based on selected examples from DiaBiz.Kom corpus, such as the use of honorifics in Polish, the use of inflection to convey meaning in Polish, the tendency to use complex sentence structures in Polish, and the cultural differences that may play a role in the annotation of dialogue acts. The article also discusses the creation of DiaBiz.Kom, a Polish dialogue corpus based on ISO 24617-2 standard applied to 1100 transcripts.

This article presents the specification and evaluation of DiaBiz.Kom – the corpus of dialogue texts in Polish. The corpus contains transcriptions of telephone conversations conducted according to a prepared scenario. The transcripts of conversations have been manually annotated with a layer of information concerning communicative functions. DiaBiz.Kom is the first corpus of this type prepared for the Polish language and will be used to develop a system of dialog analysis and modules for creating advanced chatbots.

In this article, we discuss the conditions surrounding the building of historical and literary corpora. We describe the assumptions and method of making the original corpus of the Polish novel (1864-1939). Then, we present the research procedure aimed at demonstrating the variability of the emotional value of the concept of “the city” and “the country” in the texts included in our corpus. The proposed method considers the complex socio-political nature of Central and Eastern Europe, especially the fact that there was no unified Polish state during this period. The method can be easily replicated in studies of the literature of countries with similar specificities.

In the paper, we focus on modeling spatial expressions in texts. We present the guidelines used to annotate the PST 2.0 (Corpus of Polish Spatial Texts) — a corpus designed for training and testing the tools for spatial expression recognition. The corpus contains a set of texts gathered from texts collected from travel blogs available under Creative Commons license. We have defined our guidelines based on three existing specifications for English (SpatialML, SpatialRole Labelling from SemEval-2013 Task 3 and ISO-Space1.4 from SpaceEval 2014). We briefly present the existing specifications and discuss what modifications have been made to adapt the guidelines to the characteristics of the Polish language. We also describe the process of data collection and manual annotation, including inter-annotator agreement calculation and corpus statistics. In the end, we present detailed statistics of the PST 2.0 corpus, which include the number of components, relations, expressions, and the most common values of spatial indicators, motion indicators, path indicators, distances, directions, and regions.