BMEAUT at SemEval-2020 Task 2: Lexical Entailment with Semantic Graphs
24652Authors
nan
Abstract
AbstractIn 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.
Keywords
Full Content
nan
Labeled Text
AbstractIn 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.
Publication Details
- Paper ID:
- 24652
- Year:
- 2020
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan