An analysis of entity normalization evaluation biases in specialized domains.

BACKGROUND: Entity normalization is an important information extraction task which has recently gained attention, particularly in the clinical/biomedical and life science domains. On several datasets, state-of-the-art methods perform rather well on popular benchmarks. Yet, we argue that the task is far from resolved. RESULTS: We have selected two gold standard corpora and two state-of-the-art methods to highlight some evaluation biases. We present non-exhaustive initial findings on the existence of evaluation problems of the entity normalization task. CONCLUSIONS: Our analysis suggests better evaluation practices to support the methodological research in this field.