We extract propositions from news tweets using PropS , which simplifies dependency trees by conveniently marking a wide range of predicates (e.g, verbal, adjectival, nonlexical) and positioning them as direct heads of their corresponding arguments.
we run PropS over dependency trees predicted by spaCy 6 and extract predicate types (as in Table 1) composed of verbal predicates, datives, prepositions, and auxiliaries.