  Experimental research publications provide figure form resources including
graphs, charts, and any type of images to effectively support and convey
methods and results. To describe figures, authors add captions, which are often
incomplete, and more descriptions reside in body text. This work presents a
method to extract figure descriptive text from the body of scientific articles.
We adopted ontological semantics to aid concept recognition of figure-related
information, which generates human- and machine-readable knowledge
representations from sentences. Our results show that conceptual models bring
an improvement in figure descriptive sentence classification over word-based
approaches.
