The OnomOs corpus is a linguistically processed database of texts from the periodicals Rudé právo (published 1920–1995) and Právo (1995–present). It always contains one issue from each decade in which (Rudé) Právo was published. The corpus includes texts in which the language component dominates; therefore, not included are, for example, advertisements, cinema, theatre and radio programmes, some types of texts from the sports section (e.g. scoreboards and player rosters), comics or crossword puzzles. The structure of the corpus is presented in more detail in Figure 1. In total, the corpus contains 255 149 tokens.

Figure 1 – OnomOs corpus structure (in tokens)

A specific feature of the corpus is the tagging of proper names, which could serve as a methodological basis for similar projects in the future. The annotation was done using the NameTag 2 software (Straková - Straka - Hajič, 2019; Ševčíková - Žabokrtský - Krůza, 2007; see here: https://ufal.mff.cuni.cz/nametag/2). However, the classification used by NameTag 2 was modified to be in line with the linguistic or onomastic conception of proper names (see Šrámek, 1999 and the relevant entries in the New Encyclopedic Dictionary of Czech Online: Karlík - Nekula - Pleskalová, 2017) and with current onomastic terminology. Its basis are higher-order categories, represented by anthroponyms (personal names; A), toponyms (place names/names; T) and chrématonyms (names of human products and creations; C). Each of these categories is subdivided into lower order categories (e.g. AF - family names, TT - names of territories, CF - names of companies and societies).The two-letter coding of the lower-order categories is based on their English names or similar terms (e.g. currencies are designated as CM after “money”); the letters “X” and “Y” are reserved for underspecified groups (e.g. CX). Outside the classification are terms with numerals (n), including numbers in addresses (a), and some other categories that are not considered proper nouns in the Czech tradition (e-mail addresses [me], Internet references [mi], units of measurement [oe], academic titles [pd], and most temporal terms, e.g. names of months [tm]). The transformations of NameTag 2 categories into new, onomastic classes are comprehensively presented in Table 1.

Table 1 - modification of the sorting of proper names in NameTag 2 for the purposes of the OnomOs corpus

The OnomOs corpus was created by researchers of the “Ostrava Onomastic School”, which focuses on the implementation of quantitative linguistic methods in the science of proper names within the research of the Department of Czech Language of the Faculty of Arts of the University of Ostrava. The project was supported by the grant project SGS02/FF/2023 OnomOs - Ostrava Corpus of Proper Names, which was implemented at the Faculty of Arts, University of Ostrava.

Proper nouns can be searched in the OnomOs corpus using, for example, the following command in CQL (the lower-order category is indicated in quotation marks):

[] within <ne type="TT: territories" />

The resulting concordance, which shows the territorial names, can be found in Figure 2. An abbreviated command will also suffice:

[] within <ne type="TT.*" />

If you need to search for higher-order categories, you can use, for example, the following command (the first letter of the given category – A, C, or T – is given in quotation marks):

[] within <ne type="T.*" />

An alternative approach is to display the full frequency list of lower-order categories. In this case, search for all words in the corpus (= leave the query line empty) and select “Frequency” and “Custom…” in the bar. In the frequency distribution window, we select “ According to text types” and check “ne.type”. A similar procedure can also be applied when working with subcorpora (e.g., first-republic issues of Rudé právo) or when displaying the frequencies of individual lower-order categories for a selected higher-order category (e.g., toponyms; see Figure 3).

Figure 2 - concordance of all occurrences of territory names in the OnomOs corpus.

Figure 3 - distribution of toponym types in the OnomOs corpus.

• Karlík, P. – Nekula, M. – Pleskalová, J. (2017, eds.), Nový encyklopedický slovník češtiny online. Brno: Masarykova univerzita. Dostupný z WWW: https://www.czechency.org.
• Straková, J. – Straka, M. – Hajič, J. (2019): Neural Architectures for Nested NER through Linearization. In: A. Korhonen – D. Traum – L. Màrquez (eds.), Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Florencie: Association for Computational Linguistics, s. 5326–5331.
• Ševčíková, M., Žabokrtský, Z., Krůza, O. (2007): Named Entities in Czech: Annotating Data and Developing NE Tagger. In: V. Matoušek – P. Mautner (eds), Text, Speech and Dialogue. TSD 2007. Lecture Notes in Computer Science. Berlin – Heidelberg: Springer, s. 188–195.
• Šrámek, R. (1999): Úvod do obecné onomastiky. Brno: Masarykova univerzita.