Search Results for author: Elena Simperl

Found 22 papers, 13 papers with code

Multimodal Automated Fact-Checking: A Survey

1 code implementation22 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.

Fact Checking Misinformation

A Decade of Knowledge Graphs in Natural Language Processing: A Survey

1 code implementation30 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.

Knowledge Graphs

Using Large Language Models for Knowledge Engineering (LLMKE): A Case Study on Wikidata

1 code implementation15 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.

Knowledge Probing

A Neural Network Approach for Knowledge-Driven Response Generation

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.

Response Generation

Crowdsourcing for Beyond Polarity Sentiment Analysis A Pure Emotion Lexicon

1 code implementation4 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.

Sentiment Analysis

WDV: A Broad Data Verbalisation Dataset Built from Wikidata

1 code implementation5 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.

PubHealthTab: A Public Health Table-based Dataset for Evidence-based Fact Checking

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.

Fact Checking

ChartCheck: Explainable Fact-Checking over Real-World Chart Images

1 code implementation13 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.

Fact Checking Fact Verification +1

Evaluating Large Language Models in Semantic Parsing for Conversational Question Answering over Knowledge Graphs

1 code implementation3 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.

Conversational Question Answering Information Retrieval +3

Learning to Recommend Items to Wikidata Editors

no code implementations13 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.

Collaborative Filtering Recommendation Systems

Assessing the quality of sources in Wikidata across languages: a hybrid approach

no code implementations20 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.

Descriptive

Statistical and Neural Methods for Cross-lingual Entity Label Mapping in Knowledge Graphs

no code implementations17 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.

Knowledge Graphs Machine Translation +3

ProVe: A Pipeline for Automated Provenance Verification of Knowledge Graphs against Textual Sources

no code implementations26 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.

Binary Classification Claim Verification +2

Reading and Reasoning over Chart Images for Evidence-based Automated Fact-Checking

no code implementations27 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.

Fact Checking

A Comparative Analysis of Conversational Large Language Models in Knowledge-Based Text Generation

1 code implementation2 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.

Knowledge Graphs Text Generation

Cannot find the paper you are looking for? You can Submit a new open access paper.