NER models for NameTag 2, named entity recognition tool, for English, German, Dutch, Spanish and Czech. Model documentation including performance can be found here: https://ufal.mff.cuni.cz/nametag/2/models . These models are for NameTag 2, named entity recognition tool, which can be found here: https://ufal.mff.cuni.cz/nametag/2 .
The SynSemClass synonym verb lexicon version 5.0 is a multilingual resource that enriches previous editions of this event-type ontology with a new language, Spanish. The existing languages, English, Czech and German, are further substantially extended by a larger number of classes. SSC 5.0 data also contain lists (in a separate removed_cms.zip file) with originally (pre-)proposed but later rejected class members. All languages are organized into classes and have links to other lexical sources. In addition to the existing links, links to Spanish sources have been added.
The Spanish entries are linked to
ADESSE (http://adesse.uvigo.es/),
Spanish SenSem (http://grial.edu.es/sensem/lexico?idioma=en),
Spanish WordNet (https://adimen.si.ehu.es/cgi-bin/wei/public/wei.consult.perl),
AnCora (https://clic.ub.edu/corpus/en/ancoraverb_es), and
Spanish FrameNet (http://sfn.spanishfn.org/SFNreports.php).
The English entries are linked to
EngVallex (http://hdl.handle.net/11858/00-097C-0000-0023-4337-2),
CzEngVallex (http://hdl.handle.net/11234/1-1512),
FrameNet (https://framenet.icsi.berkeley.edu/)
VerbNet (https://uvi.colorado.edu/ and http://verbs.colorado.edu/verbnet/index.html),
PropBank (http://propbank.github.io/),
Ontonotes (http://clear.colorado.edu/compsem/index.php?page=lexicalresources&sub=ontonotes), and
English Wordnet (https://wordnet.princeton.edu/).
Czech entries are linked to
PDT-Vallex (http://hdl.handle.net/11858/00-097C-0000-0023-4338-F),
Vallex (http://hdl.handle.net/11234/1-3524), and
CzEngVallex (http://hdl.handle.net/11234/1-1512).
The German entries are linked to
Woxikon (https://synonyme.woxikon.de),
E-VALBU (https://grammis.ids-mannheim.de/verbvalenz), and
GUP (http://alanakbik.github.io/multilingual.html and https://github.com/UniversalDependencies/UD_German-GSD).
Universal Derivations (UDer) is a collection of harmonized lexical networks capturing word-formation, especially derivational relations, in a cross-linguistically consistent annotation scheme for many languages. The annotation scheme is based on a rooted tree data structure, in which nodes correspond to lexemes, while edges represent derivational relations or compounding. The current version of the UDer collection contains twenty-seven harmonized resources covering twenty different languages.
Universal Derivations (UDer) is a collection of harmonized lexical networks capturing word-formation, especially derivational relations, in a cross-linguistically consistent annotation scheme for many languages. The annotation scheme is based on a rooted tree data structure, in which nodes correspond to lexemes, while edges represent derivational relations or compounding. The current version of the UDer collection contains thirty-one harmonized resources covering twenty-one different languages.
Universal Segmentations (UniSegments) is a collection of lexical resources capturing morphological segmentations harmonised into a cross-linguistically consistent annotation scheme for many languages. The annotation scheme consists of simple tab-separated columns that stores a word and its morphological segmentations, including pieces of information about the word and the segmented units, e.g., part-of-speech categories, type of morphs/morphemes etc. The current public version of the collection contains 38 harmonised segmentation datasets covering 30 different languages.
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