Abelardo Carlos Martínez Lorenzo

Hi!

I’m Carlos, a third-year PhD student at the Sapienza Natural Language Processing group, advised by Roberto Navigli and an Early Stage Researcher (ESR) at Babelscape under the Marie Skłodowska-Curie grant in the Knograph project - European Union’s Horizon 2020 research and innovation programme.

My main research focuses on Multilingual and Cross-lingual semantics, specifically on Semantic Parsing and Natural Language Generation.

I am graduated in Software Engineering by Universidad de Málaga in Spain and I pursued the Erasmus Mundus Joint Master Degree Programme in Big Data Management and Analytics (BDMA), a jointly degree delivered by Université Libre de Bruxelles (ULB) in Belgium, Universitat Politècnica de Catalunya (UPC) in Spain and Technische Universität Berlin (TU-Berlin) in Germany.

news

Mar 15, 2022	Long paper accepted at ACL 2022: “Fully-Semantic Parsing and Generation: the BabelNet Meaning Representation”. See you in Dublin!
Oct 15, 2021	Short paper accepted at AAAI 2022: “BabelNet Meaning Representation: A Fully Semantic Formalism to Overcome Language Barriers”.
Mar 1, 2021	This year I will be TA for the Natural Language Processing class at Computer Science Dept.
Nov 1, 2020	Starting a Ph.D. in Natural Language Processing + Deep Learning at the Sapienza NLP Group!

selected publications

ACL

Fully-Semantic Parsing and Generation: the BabelNet Meaning Representation

Martı́nez Lorenzo, Abelardo Carlos, Maru, Marco, and Navigli, Roberto

In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) May 2022

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A language-independent representation of meaning is one of the most coveted dreams in Natural Language Understanding. With this goal in mind, several formalisms have been proposed as frameworks for meaning representation in Semantic Parsing. And yet, the dependencies these formalisms share with respect to language-specific repositories of knowledge make the objective of closing the gap between high- and low-resourced languages hard to accomplish. In this paper, we present the BabelNet Meaning Representation (BMR), an interlingual formalism that abstracts away from language-specific constraints by taking advantage of the multilingual semantic resources of BabelNet and VerbAtlas. We describe the rationale behind the creation of BMR and put forward BMR 1.0, a dataset labeled entirely according to the new formalism. Moreover, we show how BMR is able to outperform previous formalisms thanks to its fully-semantic framing, which enables top-notch multilingual parsing and generation. We release the code at https://github.com/SapienzaNLP/bmr.
AAAI

BabelNet Meaning Representation: A Fully Semantic Formalism to Overcome Language Barriers

Navigli, Roberto, Blloshmi, Rexhina, and Martínez Lorenzo, Abelardo Carlos

Proceedings of the AAAI Conference on Artificial Intelligence Jun 2022

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