Covid-19 MLIA @ Eval initiative

doi:doi:10.57702/pc5gl618

Covid-19 MLIA @ Eval initiative

The Covid-19 MLIA @ Eval initiative consists of three Natural Language Processing tasks: information extraction, multilingual semantic search and machine translation. The goal was to organize a community evaluation effort aimed at accelerating the creation of resources and tools for improving the deployment of automatic systems focused on Covid-19 related documents.

BibTex:

@dataset{Francisco_Casacuberta_and_Alexandru_Ceausu_and_Khalid_Choukri_and_Miltos_Deligiannis_and_Miguel_Domingo_and_Mercedes_García-Martínez_and_Manuel_Herranz_and_Guillaume_Jacquet_and_Vassilis_Papavassiliou_and_Stelios_Piperidis_and_Prokopis_Prokopidis_and_Dimitris_Roussis_and_Marwa_Hadj_Salah_2024,
    abstract = {The Covid-19 MLIA @ Eval initiative consists of three Natural Language Processing tasks: information extraction, multilingual semantic search and machine translation. The goal was to organize a community evaluation effort aimed at accelerating the creation of resources and tools for improving the deployment of automatic systems focused on Covid-19 related documents.},
    author = {Francisco Casacuberta and Alexandru Ceausu and Khalid Choukri and Miltos Deligiannis and Miguel Domingo and Mercedes García-Martínez and Manuel Herranz and Guillaume Jacquet and Vassilis Papavassiliou and Stelios Piperidis and Prokopis Prokopidis and Dimitris Roussis and Marwa Hadj Salah},
    doi = {10.57702/pc5gl618},
    institution = {No Organization},
    keyword = {'Covid-19', 'Machine Translation', 'Natural Language Processing'},
    month = {dec},
    publisher = {TIB},
    title = {Covid-19 MLIA @ Eval initiative},
    url = {https://service.tib.eu/ldmservice/dataset/covid-19-mlia---eval-initiative},
    year = {2024}
}