EngVallex is the English counterpart of the PDT-Vallex valency lexicon, using the same view of valency, valency frames and the description of a surface form of verbal arguments. EngVallex contains links also to PropBank and Verbnet, two existing English predicate-argument lexicons used, i.a., for the PropBank project. The EngVallex lexicon is fully linked to the English side of the PCEDT parallel treebank, which is in fact the PTB re-annotated using the Prague Dependency Treebank style of annotation. The EngVallex is available in an XML format in our repository, and also in a searchable form with examples from the PCEDT.
EngVallex 2.0 as a slightly updated version of EngVallex. It is the English counterpart of the PDT-Vallex valency lexicon, using the same view of valency, valency frames and the description of a surface form of verbal arguments. EngVallex contains links also to PropBank (English predicate-argument lexicon). The EngVallex lexicon is fully linked to the English side of the PCEDT parallel treebank(s), which is in fact the PTB re-annotated using the Prague Dependency Treebank style of annotation. The EngVallex is available in an XML format in our repository, and also in a searchable form with examples from the PCEDT. EngVallex 2.0 is the same dataset as the EngVallex lexicon packaged with the PCEDT 3.0 corpus, but published separately under a more permissive licence, avoiding the need for LDC licence which is tied to PCEDT 3.0 as a whole.
Annotated list of dependency bigrams occurring in the PDT more than five times and having part-of-speech patterns that can possibly form a collocation. Each bigram is assigned to one of the six MWE categories by three annotators.
Moroccan Dialect Electronic Dictionary (MDED) is an electronic lexicon containing almost 15000 MSA entries. They are written in Arabic letters and translated to Moroccan Arabic dialect. In addition, MDED entries are annotated useful metadata such as POS, Origin and root. MDED can be useful in some advanced NLP applications such as Machine translation and morphological analyzer.
Mapping table for the article Hajič et al., 2024: Mapping Czech Verbal Valency to PropBank Argument Labels, in LREC-COLING 2024, as preprocess by the algorithm described in the paper. This dataset i smeant for verification (replicatoin) purposes only. It will b manually processed further to arrive at a workable CzezchpropBank, to be used in Czech UMR annotation, to be further updated during the annotation. The resulting PropBank frame files fir Czech are expected to be available with some future releases of UMR, containing Czech UMR annotation, or separately.
Czech morphological dictionary developed originally by Jan Hajič as a spelling checker and lemmatization dictionary. Currently it contains full morphological information for each covered wordform, as well as some derivational, semantic and named entity information.
Czech morphological dictionary developed originally by Jan Hajič as a spelling checker and lemmatization dictionary. Currently it contains full morphological information for each covered wordform, as well as some derivational, semantic and named entity information.
MorfFlex CZ 2.0 is the Czech morphological dictionary developed originally by Jan Hajič as a spelling checker and lemmatization dictionary. MorfFlex is a flat list of lemma-tag-wordform triples. For each wordform, full inflectional information is coded in a positional tag. Wordforms are organized into entries (paradigm instances or paradigms in short) according to their formal morphological behavior. The paradigm (set of wordforms) is identified by a unique lemma. Apart from traditional morphological categories, the description also contains some semantic, stylistic and derivational information. For more details see a comprehensive specification of the Czech morphological annotation http://ufal.mff.cuni.cz/techrep/tr64.pdf .
Slovak morphological dictionary modeled after the Czech one. It consists of (word form, lemma, POS tag) triples, reusing the Czech morphological system for POS tags and lemma descriptions.
This package comprises eight models of Czech word embeddings trained by applying word2vec (Mikolov et al. 2013) to the currently most extensive corpus of Czech, namely SYN v9 (Křen et al. 2022). The minimum frequency threshold for including a word in the model was 10 occurrences in the corpus. The original lemmatisation and tagging included in the corpus were used for disambiguation. In the case of word embeddings of word forms, units comprise word forms and their tag from a positional tagset (cf. https://wiki.korpus.cz/doku.php/en:pojmy:tag) separated by '>', e.g., kočka>NNFS1-----A----.
The published package provides models trained on both tokens and lemmas. In addition, the models combine training algorithms (CBOW and Skipgram) and dimensions of the resulting vectors (100 or 500), while the training window and negative sampling remained the same during the training. The package also includes files with frequencies of word forms (vocab-frequencies.forms) and lemmas (vocab-frequencies.lemmas).