Elena Simperl
Elena Simperl has 2 papers in our library, in 2018–2023, most of them on Language models & pretraining, Question answering, Reasoning; often with Frederique Laforest, Hady Elsahar, Oana Cocarascu.
current affiliationKing's College London, London, United Kingdom; Open Data Institute, London, United Kingdom; Technical University of Munich, Munich, Germany
OpenAlex · ORCID · h-index 38 · 441 works · 7 042 citations OpenAlex, 2026-10-14
2 works in our library · 204 citations in our library · 3 more works in our library · ⭐ Paper Star rank #3782
Affiliations
🎓King's College London
London · United Kingdom2020–2026 · 107 papers🤝Open Data Institute
London · United Kingdom2023–2026 · 29 papers🎓Technical University of Munich
Munich · Germany2025–2026 · 13 papers🎓University of Southampton
Southampton · United Kingdom2012–2020 · 120 papers🎓Karlsruhe Institute of Technology
Karlsruhe · Germany2007–2015 · 54 papers🎓Universität Innsbruck
Innsbruck · Austria2007–2013 · 32 papers🎓Freie Universität Berlin
Berlin · Germany2006–2008 · 13 papers🎓Bern University of Applied Sciences
Bern · Switzerland2021–2022 · 3 papers🤝Human Computation InstituteIthaca2014–2016 · 3 papers🔬GESIS - Leibniz Institute for the Social Sciences
Mannheim · Germany2016 · 2 papers
Topics
Works by year
2020s
2010s
Papers
- T-REx: A Large Scale Alignment of Natural Language with Knowledge Base Triples (2018 · 177 citations)
Many NLP tasks require corpora in which sentences are aligned with knowledge base (KB) triples. These include relation extraction, knowledge base population, question answering, and text generation from facts. Existing resources of this kind have shortcomings: they are too small, cover only a few predicates, or are… - Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data (2023 · 38 citations)
The authors investigate how well language models handle numbers and where exactly they make mistakes. Most previous benchmarks test only isolated aspects of numerical skills. The authors therefore propose a hierarchical taxonomy of eleven types of numerical reasoning. It has four levels, ranging from recognizing how…
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