BMEAUT at SemEval-2020 Task 2: Lexical Entailment with Semantic Graphs
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10426947" target="_blank" >RIV/00216208:11320/20:10426947 - isvavai.cz</a>
Result on the web
<a href="https://www.aclweb.org/anthology/2020.semeval-1.15" target="_blank" >https://www.aclweb.org/anthology/2020.semeval-1.15</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
BMEAUT at SemEval-2020 Task 2: Lexical Entailment with Semantic Graphs
Original language description
In this paper we present a novel rule-based, language independent method for determining lexical entailment relations using semantic representations built from Wiktionary definitions. Combined with a simple WordNet-based method our system achieves top scores on the English and Italian datasets of the Semeval-2020 task “Predicting Multilingual and Cross-lingual (graded) Lexical Entailment” (Glavaš et al., 2020). A detailed error analysis of our output uncovers future di- rections for improving both the semantic parsing method and the inference process on semantic graphs.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů