Camacho-Collados J, Delli Bovi C, Espinosa-Anke L, Oramas S, Pasini T, Santus E, Shwartz V, Navigli R, Saggion H. SemEval-2018 Task 9: Hypernym Discovery. Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval 2018)
We have relevant datasets, repositories, frameworks and tools of relevance for research and technology transfer initiatives related to knowledge extraction. This section provides an overview on a selection of them and links to download or contact details.
The MdM Strategic Research Program has its own community in Zenodo for material available in this repository
as well as at the UPF e-repository 
. Below a non-exhaustive list of datasets representative of the research in the Department.
As part of the promotion of the availability of resources, the creation of specific communities in Zenodo has also been promoted, at level of research communities (for instance, MIR and Educational Data Analytics) or MSc programs (for instance, the Master in Sound and Music Computing)
Camacho-Collados J, Delli Bovi C, Espinosa-Anke L, Oramas S, Pasini T, Santus E, Shwartz V, Navigli R, Saggion H. SemEval-2018 Task 9: Hypernym Discovery. Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval 2018)
Camacho-Collados J, Delli Bovi C, Espinosa-Anke L, Oramas S, Pasini T, Santus E, Shwartz V, Navigli R, Saggion H. SemEval-2018 Task 9: Hypernym Discovery. Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval 2018)
This paper describes the SemEval 2018 Shared Task on Hypernym Discovery. We put forward this task as a complementary benchmark for modeling hypernymy, a problem which has traditionally been cast as a binary classification task, taking a pair of candidate words as input. Instead, our reformulated task is defined as follows: given an input term, retrieve (or discover) its suitable hypernyms from a target corpus. We proposed five different subtasks covering three languages (English, Spanish, and Italian), and two specific domains of knowledge in English (Medical and Music). Participants were allowed to compete in any or all of the subtasks. Overall, a total of 11 teams participated, with a total of 39 different systems submitted through all subtasks. Data, results and further information about the task can be found at https://competitions. codalab.org/competitions/17119.