Frederique Laforest
Frederique Laforest has 2 papers in our library, in 2018–2026, most of them on Question answering, Knowledge graphs & ontologies; often with Elena Simperl, Hady Elsahar, Ludovic Moncla.
current affiliationTraces, Paris, France; Laboratoire d'Informatique en Images et Systèmes d'Information, Villeurbanne, France
OpenAlex · ORCID · h-index 17 · 185 works · 1 501 citations OpenAlex, 2026-10-14
2 works in our library · 196 citations in our library · 1 more work in our library · ⭐ Paper Star rank #3904
Affiliations
- Laboratoire d'Informatique en Images et Systèmes d'Information · Villeurbanne, France — current · 2002–2026 on 36 papers
- Traces · Paris, France — current · 2015–2026 on 23 papers
- Centre National de la Recherche Scientifique · Paris, France — 2005–2024 on 38 papers
- Institut National des Sciences Appliquées de Lyon · Lyon, France — 1998–2024 on 20 papers
- Lyon 1 Université · Villeurbanne, France — 2015–2024 on 6 papers
- Université de Lyon · Lyon, France — 2008–2021 on 24 papers
- Laboratoire Hubert Curien · Saint-Etienne, France — 2015–2018 on 36 papers
- Université Jean Monnet · Saint-Etienne, France — 2012–2018 on 26 papers
- Université Jean Monnet · Saint-Etienne, France — 2012–2018 on 16 papers
- Institut National des Sciences Appliquées de Toulouse · Toulouse, France — 2002–2011 on 3 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… - Translation from the Information Bottleneck Perspective: an Efficiency Analysis of Spatial Prepositions in Bitexts (2026)
Studies using the Information Bottleneck (IB) framework have shown that languages trade informativity against simplicity near-optimally.
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