Jaroslava Hlaváčová


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CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
Daniel Zeman | Martin Popel | Milan Straka | Jan Hajič | Joakim Nivre | Filip Ginter | Juhani Luotolahti | Sampo Pyysalo | Slav Petrov | Martin Potthast | Francis Tyers | Elena Badmaeva | Memduh Gokirmak | Anna Nedoluzhko | Silvie Cinková | Jan Hajič jr. | Jaroslava Hlaváčová | Václava Kettnerová | Zdeňka Urešová | Jenna Kanerva | Stina Ojala | Anna Missilä | 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 | Héctor Martínez Alonso | Çağrı Çöltekin | 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 | Michael Mandl | Jesse Kirchner | Hector Fernandez Alcalde | Jana Strnadová | Esha Banerjee | Ruli Manurung | Antonio Stella | Atsuko Shimada | Sookyoung Kwak | Gustavo Mendonça | Tatiana Lando | Rattima Nitisaroj | Josie Li
Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

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. In 2017, the task was devoted to learning dependency parsers for a large number of languages, in a real-world setting without any gold-standard annotation on input. All test sets followed a unified annotation scheme, namely that of Universal Dependencies. In this paper, we define the task and evaluation methodology, describe how the data sets were prepared, report and analyze the main results, and provide a brief categorization of the different approaches of the participating systems.


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Machine Translation of Medical Texts in the Khresmoi Project
Ondřej Dušek | Jan Hajič | Jaroslava Hlaváčová | Michal Novák | Pavel Pecina | Rudolf Rosa | Aleš Tamchyna | Zdeňka Urešová | Daniel Zeman
Proceedings of the Ninth Workshop on Statistical Machine Translation


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New Approach to Frequency Dictionaries - Czech Example
Jaroslava Hlaváčová
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

On the example of the recent edition of the Frequency Dictionary of Czech wedescribe and explain some new general principles that should be followed forgetting better results for practical uses of frequency dictionaries. It ismainly adopting average reduced frequency instead of absolute frequency forordering items. The formula for calculation of the average reduced frequencyis presented in the contribution together with a brief explanation, including examples clarifying the difference between the measures. Then, the Frequency Dictionary of Czech and its parts are described.


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Derivational Relations in Flectional Languages - Czech Case
Jaroslava Hlaváčová | Jana Klímová
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

When a text in any language is submitted to a morphological analysis, there always rest some unrecognized words. We can lower their number by adding new words into the dictionary used by the morphological analyzer but we can never gather the whole of the language. The system described in this paper (we call it "derivation module") deals with the unknown derived words. It aims not only at analyzing but also at synthesizing Czech derived words. Such a system is of particular value for automatic processing of languages where derivational morphology plays an important role in regular word formation.


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Rarity of Words in a Language and in a Corpus
Jaroslava Hlaváčová
Proceedings of the Second International Conference on Language Resources and Evaluation (LREC’00)