SemEval-2018 Task 7: Semantic Relation Extraction and Classification in Scientific Papers

Kata Gábor (1) , Davide Buscaldi (2) , Anne-Kathrin Schumann , Behrang Qasemizadeh (3) , Haïfa Zargayouna , Thierry Charnois (4)

1 ALPAGE - Analyse Linguistique Profonde à Grande Echelle ; Large-scale deep linguistic processing
2 LIFO - Laboratoire d'Informatique Fondamentale d'Orléans
3 Heinrich Heine Universität Düsseldorf = Heinrich Heine University [Düsseldorf]
4 Equipe CODAG - Laboratoire GREYC - UMR6072

This paper describes the first task on semantic relation extraction and classification in scientific paper abstracts at SemEval 2018. The challenge focuses on domain-specific semantic relations and includes three different sub-tasks. The subtasks were designed so as to compare and quantify the effect of different pre-processing steps on the relation classification results. We expect the task to be relevant for a broad range of researchers working on extracting specialized knowledge from domain corpora, for example but not limited to scientific or bio-medical information extraction. The task attracted a total of 32 participants, with 158 submissions across different scenarios .

Domaines: Informatique [cs]; Intelligence artificielle [cs.AI]

Kata Gábor, Davide Buscaldi, Anne-Kathrin Schumann, Behrang Qasemizadeh, Haïfa Zargayouna, et al.. SemEval-2018 Task 7: Semantic Relation Extraction and Classification in Scientific Papers. International Workshop on Semantic Evaluation (SemEval-2018), Jun 2017, New Orleans, United States. pp.679 - 688. ⟨hal-02079705⟩