  Information extraction (IE) in scientific literature has facilitated many
down-stream tasks. OpenIE, which does not require any relation schema but
identifies a relational phrase to describe the relationship between a subject
and an object, is being a trending topic of IE in sciences. The subjects,
objects, and relations are often multiword expressions, which brings challenges
for methods to identify the boundaries of the expressions given very limited or
even no training data. In this work, we present a set of rules for extracting
structured information based on dependency parsing that can be applied to any
scientific dataset requiring no expert's annotation. Results on novel datasets
show the effectiveness of the proposed method. We discuss negative results as
well.
