Work

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

Year: 2018

Type: conference-paper

Abstract: 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 subtasks.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.

Source: International Workshop on Semantic Evaluation (SemEval)

DOI: 10.18653/v1/s18-1111

Authors: Kata Gábor, Davide Buscaldi, Anne-Kathrin Schumann, Behrang QasemiZadeh, Haifa Zargayouna, Thierry Charnois

Institutions: Centre National de la Recherche Scientifique, Université Sorbonne Paris Nord, Laboratoire d'Informatique de Paris-Nord, Heinrich Heine University Düsseldorf

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: hybrid

Funders: Deutsche Forschungsgemeinschaft, Agence Nationale de la Recherche

Awards: Empirical Foundations of Linguistics : data, methods, models, G7240651115