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We present an Open Information Extraction (IE) approach that uses atwo-layered transformation stage consisting of a clausal disembedding layer anda phrasal disembedding layer, together with rhetorical relation identification.In that way, we convert sentences that present a complex linguistic structureinto simplified, syntactically sound sentences, from which we can extractpropositions that are represented in a two-layered hierarchy in the form ofcore relational tuples and accompanying contextual information which aresemantically linked via rhetorical relations. In a comparative evaluation, wedemonstrate that our reference implementation Graphene outperformsstate-of-the-art Open IE systems in the construction of correct n-arypredicate-argument structures. Moreover, we show that existing Open IEapproaches can benefit from the transformation process of our framework.

Graphene: Semantically-Linked Propositions in Open Information Extraction