Parsito is a fast open-source dependency parser written in C++. Parsito is based on greedy transition-based parsing, it has very high accuracy and achieves a throughput of 30K words per second. Parsito can be trained on any input data without feature engineering, because it utilizes artificial neural network classifier. Trained models for all treebanks from Universal Dependencies project are available (37 treebanks as of Dec 2015).
Parsito is a free software under Mozilla Public License 2.0 (http://www.mozilla.org/MPL/2.0/) and the linguistic models are free for non-commercial use and distributed under CC BY-NC-SA (http://creativecommons.org/licenses/by-nc-sa/4.0/) license, although for some models the original data used to create the model may impose additional licensing conditions.
Parsito website http://ufal.mff.cuni.cz/parsito contains download links of both
the released packages and trained models, hosts documentation and offers online
demo.
Parsito development repository http://github.com/ufal/parsito is hosted on
GitHub.
PAWS is a multi-lingual parallel treebank with coreference annotation. It consists of English texts from the Wall Street Journal translated into Czech, Russian and Polish. In addition, the texts are syntactically parsed and word-aligned. PAWS is based on PCEDT 2.0 and continues the tradition of multilingual treebanks with coreference annotation. PAWS offers linguistic material that can be further leveraged in cross-lingual studies, especially on coreference.
The valency lexicon PDT-Vallex has been built in close connection with the annotation of the Prague Dependency Treebank project (PDT) and its successors (mainly the Prague Czech-English Dependency Treebank project, PCEDT). It contains over 11000 valency frames for more than 7000 verbs which occurred in the PDT or PCEDT. It is available in electronically processable format (XML) together with the aforementioned treebanks (to be viewed and edited by TrEd, the PDT/PCEDT main annotation tool), and also in more human readable form including corpus examples (see the WEBSITE link below). The main feature of the lexicon is its linking to the annotated corpora - each occurrence of each verb is linked to the appropriate valency frame with additional (generalized) information about its usage and surface morphosyntactic form alternatives.
The valency lexicon PDT-Vallex 4.0 has been built in close connection with the annotation of the Prague Dependency Treebank project (PDT) and its successors (mainly the Prague Czech-English Dependency Treebank project, PCEDT, the spoken language corpus (PDTSC) and corpus of user-generated texts in the project Faust). It contains over 14500 valency frames for almost 8500 verbs which occurred in the PDT, PCEDT, PDTSC and Faust corpora. In addition, there are nouns, adjectives and adverbs, linked from the PDT part only, increasing the total to over 17000 valency frames for 13000 words. All the corpora have been published in 2020 as the PDT-C 1.0 corpus with the PDT-Vallex 4.0 dictionary included; this is a copy of the dictionary published as a separate item for those not interested in the corpora themselves. It is available in electronically processable format (XML), and also in more human readable form including corpus examples (see the WEBSITE link below, and the links to its main publications elsewhere in this metadata). The main feature of the lexicon is its linking to the annotated corpora - each occurrence of each verb is linked to the appropriate valency frame with additional (generalized) information about its usage and surface morphosyntactic form alternatives. It replaces the previously published unversioned edition of PDT-Vallex from 2014.
The segment of Československý zvukový týdeník Aktualita (Czechoslovak Aktualita Sound Newsreel), 1938, issue no. 27 reports on the 16th International Congress of PEN. Clubs held in Prague from 26 to 30 June 1938. The delegates include President Edvard Beneš and his wife Hana, the writers Karel Čapek, H. G. Wells and Olga Scheinpflugová, and Vojtěch Mastný, the Czechoslovak envoy to Berlin.