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 develop a large number of software tools and hosting infrastructures to support the research developed at the Department. We will be detailing in this section the different tools available. You can take a look for the moment at the offer available within the UPF Knowledge Portal, the innovations created in the context of EU projects in the Innovation Radar and the software sections of some of our research groups:
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Artificial Intelligence |
Nonlinear Time Series Analysis |
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Music Technology |
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Barcelona MedTech |
Natural Language Processing |
Nonlinear Time Series Analysis |
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UbicaLab |
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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.