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Over the last five years, research on Relation Extraction (RE) witnessedextensive progress with many new dataset releases. At the same time, setupclarity has decreased, contributing to increased difficulty of reliableempirical evaluation (Taill\'e et al., 2020). In this paper, we provide acomprehensive survey of RE datasets, and revisit the task definition and itsadoption by the community. We find that cross-dataset and cross-domain setupsare particularly lacking. We present an empirical study on scientific RelationClassification across two datasets. Despite large data overlap, our analysisreveals substantial discrepancies in annotation. Annotation discrepanciesstrongly impact Relation Classification performance, explaining large drops incross-dataset evaluations. Variation within further sub-domains exists butimpacts Relation Classification only to limited degrees. Overall, our studycalls for more rigour in reporting setups in RE and evaluation across multipletest sets.

What do You Mean by Relation Extraction? A Survey on Datasets and Study on Scientific Relation Classification