# The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures

## TL;DR

This paper introduces a new annotated dataset of materials synthesis procedures in scientific text, enabling better extraction of structured information for scientific analysis and automation.

## Contribution

The authors present a novel, expert-annotated corpus of materials synthesis procedures with semantic graphs, facilitating research in automated information extraction from scientific literature.

## Key findings

- Created a dataset of 230 annotated synthesis procedures
- Highlighted challenges in annotating scientific text with semantic structures
- Made the corpus publicly available for research use

## Abstract

Materials science literature contains millions of materials synthesis procedures described in unstructured natural language text. Large-scale analysis of these synthesis procedures would facilitate deeper scientific understanding of materials synthesis and enable automated synthesis planning. Such analysis requires extracting structured representations of synthesis procedures from the raw text as a first step. To facilitate the training and evaluation of synthesis extraction models, we introduce a dataset of 230 synthesis procedures annotated by domain experts with labeled graphs that express the semantics of the synthesis sentences. The nodes in this graph are synthesis operations and their typed arguments, and labeled edges specify relations between the nodes. We describe this new resource in detail and highlight some specific challenges to annotating scientific text with shallow semantic structure. We make the corpus available to the community to promote further research and development of scientific information extraction systems.