Kévin Cousot

Also published as: Kevin Cousot


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Introducing RezoJDM16k: a French KnowledgeGraph DataSet for Link Prediction
Mehdi Mirzapour | Waleed Ragheb | Mohammad Javad Saeedizade | Kevin Cousot | Helene Jacquenet | Lawrence Carbon | Mathieu Lafourcade
Proceedings of the Thirteenth Language Resources and Evaluation Conference

Knowledge graphs applications, in industry and academia, motivate substantial research directions towards large-scale information extraction from various types of resources. Nowadays, most of the available knowledge graphs are either in English or multilingual. In this paper, we introduce RezoJDM16k, a French knowledge graph dataset based on RezoJDM. With 16k nodes, 832k triplets, and 53 relation types, RezoJDM16k can be employed in many NLP downstream tasks for the French language such as machine translation, question-answering, and recommendation systems. Moreover, we provide strong knowledge graph embedding baselines that are used in link prediction tasks for future benchmarking. Compared to the state-of-the-art English knowledge graph datasets used in link prediction, RezoJDM16k shows a similar promising predictive behavior.


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A Dataset for Anaphora Analysis in French Emails
Hani Guenoune | Kevin Cousot | Mathieu Lafourcade | Melissa Mekaoui | Cédric Lopez
Proceedings of the Third Workshop on Computational Models of Reference, Anaphora and Coreference

In 2019, about 293 billion emails were sent worldwide every day. They are a valuable source of information and knowledge for professionals. Since the 90’s, many studies have been done on emails and have highlighted the need for resources regarding numerous NLP tasks. Due to the lack of available resources for French, very few studies on emails have been conducted. Anaphora resolution in emails is an unexplored area, annotated resources are needed, at least to answer a first question: Does email communication have specifics that must be addressed to tackle the anaphora resolution task? In order to answer this question 1) we build a French emails corpus composed of 100 anonymized professional threads and make it available freely for scientific exploitation. 2) we provide annotations of anaphoric links in the email collection.


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JeuxDeLiens: Word Embeddings and Path-Based Similarity for Entity Linking using the French JeuxDeMots Lexical Semantic Network
Julien Plu | Kevin Cousot | Mathieu Lafourcade | Raphaël Troncy | Giuseppe Rizzo
Actes de la Conférence TALN. Volume 1 - Articles longs, articles courts de TALN

Entity linking systems typically rely on encyclopedic knowledge bases such as DBpedia or Freebase. In this paper, we use, instead, a French lexical-semantic network named JeuxDeMots to jointly type and link entities. Our approach combines word embeddings and a path-based similarity resulting in encouraging results over a set of documents from the French Le Monde newspaper.


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Explicative Path Finding in a Semantic Network
Kévin Cousot | Mathieu Lafourcade
Proceedings of the Computing Natural Language Inference Workshop