R eact IE : Enhancing Chemical Reaction Extraction with Weak Supervision (2023)

Abstract: Structured chemical reaction information plays a vital role for chemists engaged in laboratory work and advanced endeavors such as computer-aided drug design. Despite the importance of extracting structured reactions from scientific literature, data annotation for this purpose is cost-prohibitive due to the significant labor required from domain experts. Consequently, the scarcity of sufficient training data poses an obstacle to the progress of related models in this domain. In this paper, we propose ReactIE, which combines two weakly supervised approaches for pre-training. Our method utilizes frequent patterns within the text as linguistic cues to identify specific characteristics of chemical reactions. Additionally, we adopt synthetic data from patent records as distant supervision to incorporate domain knowledge into the model. Experiments demonstrate that ReactIE achieves substantial improvements and outperforms all existing baselines.

## introduction the integration of advanced natural language processing (nlp) techniques in the field of chemistry has been gaining significant attention in both academia and industry @xcite @xcite . by formulating applications in chemistry as molecular representation @xcite , information extraction @xcite @xcite , and text generation @xcite tasks, nlp approaches provide new avenues for effective understanding and analysis of chemical information. in particular, we focus on the chemical reaction extraction task, as it can serve as a valuable reference for chemists to conduct bench experiments @xcite . despite the abundance of text describing chemical reactions in the scientific literature, the conversion to a structured format remains a major challenge. one approach is the utilization of domain ## conclusion in this paper, we present reactie, an automatic framework for extracting chemical reactions from the scientific literature. our approach incorporates linguistic and chemical knowledge into the pre-training. experiments show that reactie achieves state-of-the-art results by a large margin.