International audienceWe present a study in which we compare 11 different French dependency parsers on a specialized corpus (consisting of research articles on NLP from the proceedings of the TALN conference). Due to the lack of a suitable gold standard, we use each of the parsers' output to generate distributional thesauri using a frequency-based method. We compare these 11 thesauri to assess the impact of choosing a parser over another. We show that, without any reference data, we can still identify relevant subsets among the different parsers. We also show that the similarity we identify between parsers is confirmed on a restricted distributional benchmark
International audienceIn this article we present FreDist, a freely available software package for th...
International audienceIn this article we present FreDist, a freely available software package for th...
International audienceDistributional semantics models can be built using simple bag-of-word represen...
International audienceWe present a study in which we compare 11 different French dependency parsers ...
International audienceWe present a study in which we compare 11 different French dependency parsers ...
International audienceWe present a study in which we compare 11 different French dependency parsers ...
International audienceWe present a study with the goal of comparing 11 different french dependency p...
International audienceWe present a study with the goal of comparing 11 different french dependency p...
International audienceWe present a study with the goal of comparing 11 different french dependency p...
International audienceWe present a study with the goal of comparing 11 different french dependency p...
9 pagesInternational audienceWe compare the performance of three statistical parsing architectures o...
Résumé. Dans cet article, nous présentons FreDist, un logiciel libre pour la construction automatiqu...
International audienceIn this article we present FreDist, a freely available software package for th...
9 pagesInternational audienceWe compare the performance of three statistical parsing architectures o...
9 pagesInternational audienceWe compare the performance of three statistical parsing architectures o...
International audienceIn this article we present FreDist, a freely available software package for th...
International audienceIn this article we present FreDist, a freely available software package for th...
International audienceDistributional semantics models can be built using simple bag-of-word represen...
International audienceWe present a study in which we compare 11 different French dependency parsers ...
International audienceWe present a study in which we compare 11 different French dependency parsers ...
International audienceWe present a study in which we compare 11 different French dependency parsers ...
International audienceWe present a study with the goal of comparing 11 different french dependency p...
International audienceWe present a study with the goal of comparing 11 different french dependency p...
International audienceWe present a study with the goal of comparing 11 different french dependency p...
International audienceWe present a study with the goal of comparing 11 different french dependency p...
9 pagesInternational audienceWe compare the performance of three statistical parsing architectures o...
Résumé. Dans cet article, nous présentons FreDist, un logiciel libre pour la construction automatiqu...
International audienceIn this article we present FreDist, a freely available software package for th...
9 pagesInternational audienceWe compare the performance of three statistical parsing architectures o...
9 pagesInternational audienceWe compare the performance of three statistical parsing architectures o...
International audienceIn this article we present FreDist, a freely available software package for th...
International audienceIn this article we present FreDist, a freely available software package for th...
International audienceDistributional semantics models can be built using simple bag-of-word represen...