[4Rin1] Interactive 2

[4Rin1-12] Synthesis Process Paragraph Extraction from Scientific Literature of Inorganic Material

〇Kohei Makino^1,3, Fusataka Kuniyoshi^2,3, Jun Ozawa^2,3, Makoto Miwa^1,3 (1.Toyota Technological Institute, 2.Panasonic Corporation, 3.National Institute of Advanced Industrial Science and Technology)

Keywords:Paragraph Extraction, Natural Language Processing, Materials Informatics

In the field of inorganic materials, there is a need for a system that supports development by analyzing synthesis processes described in a large number of papers. In order to realize the system, it is necessary to extract the part where synthesis processes are described from the papers. We propose a tool that extracts paragraphs describing synthesis processes from papers in the PDF format. We develop the tool by combining a deep learning-based sentence classifier that determines whether each sentence includes synthesis processes or not and a paragraph detector using the sentence classifier. In the experiment, we evaluated our tool on manually-labeled 300 papers. As a result, our tool performed well in both classifying sentences and detecting paragraphs. This result shows that the proposed tool is useful in extracting paragraphs on synthesis processes.