BMEAUT at SemEval-2020 Task 2: Lexical entailment with semantic graphs
Ádám Kovács, Kinga Gémes, András Kornai, Gábor Recski
In Proceedings of the 14th International Workshop on Semantic Evaluation,
2020
ACLWEB
PDF
ACLWEB
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" (Glavas et. al. 2020). A detailed error analysis of our output uncovers future directions for improving both the semantic parsing method and the inference process on semantic graphs.
Citation
@inproceedings{Kovacs:2020a,
title = "{BMEAUT} at {S}em{E}val-2020 Task 2: Lexical Entailment with Semantic Graphs",
author = "Kov\'acs, {\'A}d{\'a}m and
G{\'e}mes, Kinga and
Kornai, Andras and
Recski, G{\'a}bor",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.semeval-1.15",
pages = "135--141",
}