no code implementations • LREC 2022 • Lukáš Kyjánek, Olga Lyashevskaya, Anna Nedoluzhko, Daniil Vodolazsky, Zdeněk Žabokrtský
Therefore, we devote this paper to improving one of the methods of constructing such resources and to the application of the method to a Russian lexicon, which results in the creation of the largest lexical resource of Russian derivational relations.
no code implementations • LREC 2022 • Anna Nedoluzhko, Michal Novák, Martin Popel, Zdeněk Žabokrtský, Amir Zeldes, Daniel Zeman
Recent advances in standardization for annotated language resources have led to successful large scale efforts, such as the Universal Dependencies (UD) project for multilingual syntactically annotated data.
no code implementations • LREC 2022 • Anna Nedoluzhko, Muskaan Singh, Marie Hledíková, Tirthankar Ghosal, Ondřej Bojar
Our dataset, AutoMin, consists of 113 (English) and 53 (Czech) meetings, covering more than 160 hours of meeting content.
no code implementations • Findings (EMNLP) 2021 • Martin Popel, Zdeněk Žabokrtský, Anna Nedoluzhko, Michal Novák, Daniel Zeman
One can find dozens of data resources for various languages in which coreference - a relation between two or more expressions that refer to the same real-world entity - is manually annotated.
1 code implementation • 21 Oct 2024 • Michal Novák, Barbora Dohnalová, Miloslav Konopík, Anna Nedoluzhko, Martin Popel, Ondřej Pražák, Jakub Sido, Milan Straka, Zdeněk Žabokrtský, Daniel Zeman
The paper presents an overview of the third edition of the shared task on multilingual coreference resolution, held as part of the CRAC 2024 workshop.
1 code implementation • CRAC (ACL) 2022 • Zdeněk Žabokrtský, Miloslav Konopík, Anna Nedoluzhko, Michal Novák, Maciej Ogrodniczuk, Martin Popel, Ondřej Pražák, Jakub Sido, Daniel Zeman, YIlun Zhu
The public edition of CorefUD 1. 0, which contains 13 datasets for 10 languages, was used as the source of training and evaluation data.
no code implementations • LREC 2022 • Peter Polák, Muskaan Singh, Anna Nedoluzhko, Ondřej Bojar
To facilitate the research in this area, we present ALIGNMEET, a comprehensive tool for meeting annotation, alignment, and evaluation.
no code implementations • WS 2018 • Anna Nedoluzhko, Michal Nov{\'a}k, Maciej Ogrodniczuk
We present PAWS, a multi-lingual parallel treebank with coreference annotation.
no code implementations • CONLL 2017 • Daniel Zeman, Martin Popel, Milan Straka, Jan Haji{\v{c}}, Joakim Nivre, Filip Ginter, Juhani Luotolahti, Sampo Pyysalo, Slav Petrov, Martin Potthast, Francis Tyers, Elena Badmaeva, Memduh Gokirmak, Anna Nedoluzhko, Silvie Cinkov{\'a}, Jan Haji{\v{c}} jr., Jaroslava Hlav{\'a}{\v{c}}ov{\'a}, V{\'a}clava Kettnerov{\'a}, Zde{\v{n}}ka Ure{\v{s}}ov{\'a}, Jenna Kanerva, Stina Ojala, Anna Missil{\"a}, Christopher D. Manning, Sebastian Schuster, Siva Reddy, Dima Taji, Nizar Habash, Herman Leung, Marie-Catherine de Marneffe, Manuela Sanguinetti, Maria Simi, Hiroshi Kanayama, Valeria de Paiva, Kira Droganova, H{\'e}ctor Mart{\'\i}nez Alonso, {\c{C}}a{\u{g}}r{\i} {\c{C}}{\"o}ltekin, Umut Sulubacak, Hans Uszkoreit, Vivien Macketanz, Aljoscha Burchardt, Kim Harris, Katrin Marheinecke, Georg Rehm, Tolga Kayadelen, Mohammed Attia, Ali Elkahky, Zhuoran Yu, Emily Pitler, Saran Lertpradit, M, Michael l, Jesse Kirchner, Hector Fern Alcalde, ez, Jana Strnadov{\'a}, Esha Banerjee, Ruli Manurung, Antonio Stella, Atsuko Shimada, Sookyoung Kwak, Gustavo Mendon{\c{c}}a, L, Tatiana o, Rattima Nitisaroj, Josie Li
The Conference on Computational Natural Language Learning (CoNLL) features a shared task, in which participants train and test their learning systems on the same data sets.
no code implementations • WS 2017 • Michal Nov{\'a}k, Anna Nedoluzhko, Zden{\v{e}}k {\v{Z}}abokrtsk{\'y}
The paper describes the system for coreference resolution in German and Russian, trained exclusively on coreference relations project ed through a parallel corpus from English.
no code implementations • WS 2016 • Anna Nedoluzhko
The paper presents a contrastive description of reflexive possessive pronouns {``}sv{\r{u}}j{''} in Czech and {``}svoj{''} in Russian.
1 code implementation • LREC 2016 • Anna Nedoluzhko, Michal Nov{\'a}k, Silvie Cinkov{\'a}, Marie Mikulov{\'a}, Ji{\v{r}}{\'\i} M{\'\i}rovsk{\'y}
We present coreference annotation on parallel Czech-English texts of the Prague Czech-English Dependency Treebank (PCEDT).
no code implementations • LREC 2016 • Ekaterina Lapshinova-Koltunski, Kerstin Anna Kunz, Anna Nedoluzhko
We use an interoperable scheme unifying discourse phenomena in both frameworks into more abstract categories and considering only those phenomena that have a direct match in German and Czech.