Carlos Bobed Lisbona — accepted AI-conference papers

2024

Building MUSCLE, a Dataset for MUltilingual Semantic Classification of Links between Entities

Lucia Pitarch, Carlos Bobed Lisbona, David Abián, Jorge Gracia, Jordi Bernad

COLING 2024main

In this paper we introduce MUSCLE, a dataset for MUltilingual lexico-Semantic Classification of Links between Entities. The MUSCLE dataset was designed to train and evaluate Lexical Relation Classification (LRC) systems with 27K pairs of universal concepts selected from Wikidata, a large and highly…

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗

2023

No clues good clues: out of context Lexical Relation Classification

Lucia Pitarch, Jordi Bernad, Lacramioara Dranca, Carlos Bobed Lisbona, Jorge Gracia

ACL 2023long

The accurate prediction of lexical relations between words is a challenging task in Natural Language Processing (NLP). The most recent advances in this direction come with the use of pre-trained language models (PTLMs). A PTLM typically needs “well-formed” verbalized text to interact with it, either…

Cited by 6 Source ↗PDF ↗Scholar ↗