This paper deals with an automatic part-of-speech disambiguation of Czech texts containing the word to (E. it) in fixed collocations used especially in spoken Czech, and, moreover, with case identification of the pronominal reading of this word. The word to is ambiguous: the result of automatic morphological analysis of this word is either the pronominal lemma ten (it) as a nominative/accusative singular neuter, or the particle lemma to. It is very difficult to automatically distinguish the nonprepositional nominative and accusative case in Czech texts. Therefore, the paper primarily focuses on to as a particle. The software module performing automatic identification of collocations in Czech corpus texts is part of the automatic morphological rule-based disambiguation used for tagging texts of synchronic Czech in the corpora of the SYN series: it deals mainly with the disam-biguation of nongrammatical collocations and phrases. The paper focuses on fixed ex-pressions listed in the Dictionary of Czech Phraseology and Idiomatics and is based on the description of automatic identification and classification of collocations comprising the word to in the SYN2010 corpus. Also, examples (primarily idioms) are presented where automatic disambiguation using general grammatical rules yields unreliable results.
In NLP Centre, dividing text into sentences is currently done with
a tool which uses rule-based system. In order to make enough training
data for machine learning, annotators manually split the corpus of contemporary text
CBB.blog (1 million tokens) into sentences.
Each file contains one hundredth of the whole corpus and all data were
processed in parallel by two annotators.
The corpus was created from ten contemporary blogs:
hintzu.otaku.cz
modnipeklo.cz
bloc.cz
aleneprokopova.blogspot.com
blog.aktualne.cz
fuchsova.blog.onaidnes.cz
havlik.blog.idnes.cz
blog.aktualne.centrum.cz
klusak.blogspot.cz
myego.cz/welldone
CsEnVi Pairwise Parallel Corpora consist of Vietnamese-Czech parallel corpus and Vietnamese-English parallel corpus. The corpora were assembled from the following sources:
- OPUS, the open parallel corpus is a growing multilingual corpus of translated open source documents.
The majority of Vi-En and Vi-Cs bitexts are subtitles from movies and television series.
The nature of the bitexts are paraphrasing of each other's meaning, rather than translations.
- TED talks, a collection of short talks on various topics, given primarily in English, transcribed and with transcripts translated to other languages. In our corpus, we use 1198 talks which had English and Vietnamese transcripts available and 784 talks which had Czech and Vietnamese transcripts available in January 2015.
The size of the original corpora collected from OPUS and TED talks is as follows:
CS/VI EN/VI
Sentence 1337199/1337199 2035624/2035624
Word 9128897/12073975 16638364/17565580
Unique word 224416/68237 91905/78333
We improve the quality of the corpora in two steps: normalizing and filtering.
In the normalizing step, the corpora are cleaned based on the general format of subtitles and transcripts. For instance, sequences of dots indicate explicit continuation of subtitles across multiple time frames. The sequences of dots are distributed differently in the source and the target side. Removing the sequence of dots, along with a number of other normalization rules, improves the quality of the alignment significantly.
In the filtering step, we adapt the CzEng filtering tool [1] to filter out bad sentence pairs.
The size of cleaned corpora as published is as follows:
CS/VI EN/VI
Sentence 1091058/1091058 1113177/1091058
Word 6718184/7646701 8518711/8140876
Unique word 195446/59737 69513/58286
The corpora are used as training data in [2].
References:
[1] Ondřej Bojar, Zdeněk Žabokrtský, et al. 2012. The Joy of Parallelism with CzEng 1.0. Proceedings of LREC2012. ELRA. Istanbul, Turkey.
[2] Duc Tam Hoang and Ondřej Bojar, The Prague Bulletin of Mathematical Linguistics. Volume 104, Issue 1, Pages 75–86, ISSN 1804-0462. 9/2015
Web corpus of Czech, created in 2011. Contains newspapers+magazines, discussions, blogs. See http://www.lrec-conf.org/proceedings/lrec2012/summaries/120.html for details. and GA405/09/0278
We present the Czech Court Decisions Dataset (CCDD) -- a dataset of 300 manually annotated court decisions published by The Supreme Court of the Czech Republic and the Constitutional Court of the Czech Republic.
The Czech Legal Text Treebank (CLTT) is a collection of 1133 manually annotated dependency trees. CLTT consists of two legal documents: The Accounting Act (563/1991 Coll., as amended) and Decree on Double-entry Accounting for undertakers (500/2002 Coll., as amended).
The package contains Czech recordings of the Visual History Archive which consists of the interviews with the Holocaust survivors. The archive consists of audio recordings, four types of automatic transcripts, manual annotations of selected topics and interviews' metadata. The archive totally contains 353 recordings and 592 hours of interviews.
The presented Czech Named Entity Corpus 1.0 is the first publicly available corpus providing a large body of manually annotated named entities in Czech sentences, including a fine-grained classification. and 1ET101120503 (Integrace jazykových zdrojů za účelem extrakce informací z přirozených textů)
Czech Named Entity Corpus 1.1 fixes some issues of the Czech Named Entity Corpus 1.0: misannotated entities are fixed, all formats contain the same data, tmt format is replaced with treex format, all formats contain splitting into training, development and testing portion of the data. and SVV 267 314 (Teoretické základy informatiky a výpočetní lingvistiky), LM2010013 (LINDAT-CLARIN: Institut pro analýzu, zpracování a distribuci lingvistických dat), GPP406/12/P175 (Vybrané derivační vztahy pro automatické zpracování češtiny), PRVOUK (PRVOUK)