1 code implementation • 22 May 2023 • Mubashara Akhtar, Michael Schlichtkrull, Zhijiang Guo, Oana Cocarascu, Elena Simperl, Andreas Vlachos
In this survey, we conceptualise a framework for AFC including subtasks unique to multimodal misinformation.
1 code implementation • 30 Sep 2022 • Phillip Schneider, Tim Schopf, Juraj Vladika, Mikhail Galkin, Elena Simperl, Florian Matthes
In pace with developments in the research field of artificial intelligence, knowledge graphs (KGs) have attracted a surge of interest from both academia and industry.
1 code implementation • 15 Sep 2023 • Bohui Zhang, Ioannis Reklos, Nitisha Jain, Albert Meroño Peñuela, Elena Simperl
In this work, we explore the use of Large Language Models (LLMs) for knowledge engineering tasks in the context of the ISWC 2023 LM-KBC Challenge.
1 code implementation • 1 Nov 2017 • Pavlos Vougiouklis, Hady Elsahar, Lucie-Aimée Kaffee, Christoph Gravier, Frederique Laforest, Jonathon Hare, Elena Simperl
We explore the problem of generating natural language summaries for Semantic Web data.
1 code implementation • COLING 2016 • Pavlos Vougiouklis, Jonathon Hare, Elena Simperl
Our model is based on a Recurrent Neural Network (RNN) that is trained over concatenated sequences of comments, a Convolution Neural Network that is trained over Wikipedia sentences and a formulation that couples the two trained embeddings in a multimodal space.
1 code implementation • 4 Oct 2017 • Giannis Haralabopoulos, Elena Simperl
For these methods to work, they require a critical resource: a lexicon that is appropriate for the task at hand, in terms of the range of emotions it captures diversity.
1 code implementation • NAACL 2018 • Lucie-Aimée Kaffee, Hady Elsahar, Pavlos Vougiouklis, Christophe Gravier, Frédérique Laforest, Jonathon Hare, Elena Simperl
While Wikipedia exists in 287 languages, its content is unevenly distributed among them.
1 code implementation • 5 May 2022 • Gabriel Amaral, Odinaldo Rodrigues, Elena Simperl
Data verbalisation is a task of great importance in the current field of natural language processing, as there is great benefit in the transformation of our abundant structured and semi-structured data into human-readable formats.
1 code implementation • Findings (NAACL) 2022 • Mubashara Akhtar, Oana Cocarascu, Elena Simperl
Inspired by human fact checkers, who use different types of evidence (e. g. tables, images, audio) in addition to text, several datasets with tabular evidence data have been released in recent years.
1 code implementation • 13 Nov 2023 • Mubashara Akhtar, Nikesh Subedi, Vivek Gupta, Sahar Tahmasebi, Oana Cocarascu, Elena Simperl
Whilst fact verification has attracted substantial interest in the natural language processing community, verifying misinforming statements against data visualizations such as charts has so far been overlooked.
1 code implementation • 3 Jan 2024 • Phillip Schneider, Manuel Klettner, Kristiina Jokinen, Elena Simperl, Florian Matthes
Conversational question answering systems often rely on semantic parsing to enable interactive information retrieval, which involves the generation of structured database queries from a natural language input.
no code implementations • 13 Jul 2021 • Kholoud Alghamdi, Miaojing Shi, Elena Simperl
The system uses a hybrid of content-based and collaborative filtering techniques to rank items for editors relying on both item features and item-editor previous interaction.
no code implementations • 20 Sep 2021 • Gabriel Amaral, Alessandro Piscopo, Lucie-Aimée Kaffee, Odinaldo Rodrigues, Elena Simperl
Wikidata is one of the most important sources of structured data on the web, built by a worldwide community of volunteers.
no code implementations • 17 Jun 2022 • Gabriel Amaral, Mārcis Pinnis, Inguna Skadiņa, Odinaldo Rodrigues, Elena Simperl
However, such labels are not guaranteed to match across languages from an information consistency standpoint, greatly compromising their usefulness for fields such as machine translation.
no code implementations • 26 Oct 2022 • Gabriel Amaral, Odinaldo Rodrigues, Elena Simperl
Knowledge Graphs are repositories of information that gather data from a multitude of domains and sources in the form of semantic triples, serving as a source of structured data for various crucial applications in the modern web landscape, from Wikipedia infoboxes to search engines.
no code implementations • 4 Dec 2022 • Kholoud Alghamdi, Miaojing Shi, Elena Simperl
Our aim with this paper is to elicit the user requirements for a Wikidata recommendations system.
no code implementations • 27 Jan 2023 • Mubashara Akhtar, Oana Cocarascu, Elena Simperl
Evidence data for automated fact-checking (AFC) can be in multiple modalities such as text, tables, images, audio, or video.
no code implementations • 3 Nov 2023 • Mubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta, Arpit Patil, Oana Cocarascu, Elena Simperl
Thus, understanding and reasoning with numbers are essential skills for language models to solve different tasks.
1 code implementation • 2 Feb 2024 • Phillip Schneider, Manuel Klettner, Elena Simperl, Florian Matthes
In this study, we conduct an empirical analysis of conversational large language models in generating natural language text from semantic triples.
no code implementations • 28 Mar 2024 • Mubashara Akhtar, Omar Benjelloun, Costanza Conforti, Joan Giner-Miguelez, Nitisha Jain, Michael Kuchnik, Quentin Lhoest, Pierre Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Pierre Ruyssen, Rajat Shinde, Elena Simperl, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren, Steffen Vogler, Carole-Jean Wu
Data is a critical resource for Machine Learning (ML), yet working with data remains a key friction point.