SynSemClass Linked Lexicon: Mapping Synonymy between Languages

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10424504" target="_blank" >RIV/00216208:11320/20:10424504 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.aclweb.org/anthology/2020.globalex-1.2" target="_blank" >https://www.aclweb.org/anthology/2020.globalex-1.2</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

SynSemClass Linked Lexicon: Mapping Synonymy between Languages

Popis výsledku v původním jazyce

This lexicon stores cross-lingual semantically similar verb senses in synonym classes extracted from a richly annotated parallel corpus, the Prague Czech-English Dependency Treebank. When building the lexicon, we make use of predicate-argument relations (valency) and link them to semantic roles; in addition, each entry is linked to several external lexicons of more or less &quot;semantic&quot; nature, namely FrameNet, WordNet, VerbNet, OntoNotes and PropBank, and Czech VALLEX. The aim is to provide a linguistic resource that can be used to compare semantic roles and their syntactic properties and features across languages within and across synonym groups (classes, or &apos;synsets&apos;), as well as gold standard data for automatic NLP experiments with such synonyms, such as synonym discovery, feature mapping, etc. However, perhaps the most important goal is to eventually build an event type ontology that can be referenced and used as a human-readable and human-understandable &quot;database&quot; for all types of events, processes

Název v anglickém jazyce

SynSemClass Linked Lexicon: Mapping Synonymy between Languages

Popis výsledku anglicky

This lexicon stores cross-lingual semantically similar verb senses in synonym classes extracted from a richly annotated parallel corpus, the Prague Czech-English Dependency Treebank. When building the lexicon, we make use of predicate-argument relations (valency) and link them to semantic roles; in addition, each entry is linked to several external lexicons of more or less &quot;semantic&quot; nature, namely FrameNet, WordNet, VerbNet, OntoNotes and PropBank, and Czech VALLEX. The aim is to provide a linguistic resource that can be used to compare semantic roles and their syntactic properties and features across languages within and across synonym groups (classes, or &apos;synsets&apos;), as well as gold standard data for automatic NLP experiments with such synonyms, such as synonym discovery, feature mapping, etc. However, perhaps the most important goal is to eventually build an event type ontology that can be referenced and used as a human-readable and human-understandable &quot;database&quot; for all types of events, processes

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2020 Globalex Workshop on Linked Lexicography (LREC 2020)

ISBN

979-10-95546-46-7

ISSN

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e-ISSN

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Počet stran výsledku

10

Strana od-do

10-19

Název nakladatele

European Language Resources Association

Místo vydání

Marseille, France

Místo konání akce

Marseille, France

Datum konání akce

12. 5. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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