Snowball 2.0: Generic Material Data Parser for ChemDataExtractor.

ABSTRACT: The ever-growing amount of chemical data found in the scientific literature has led to the emergence of data-driven materials discovery. The first step in the pipeline, to automatically extract chemical information from plain text, has been driven by the development of software toolkits such as ChemDataExtractor. Such data extraction processes have created a demand for parsers that efficiently enable text mining. Here, we present Snowball 2.0, a sentence parser based on a semisupervised machine-learning algorithm. It can be used to extract any chemical property without additional training. We validate its precision, recall, and F-score by training and testing a model with sentences of semiconductor band gap information curated from journal articles. Snowball 2.0 builds on two previo

SUBMITTER: Dong Q 

PROVIDER: S-EPMC10685441 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature