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Found 8 papers, 5 papers with code
Discourse-Aware Text Simplification: From Complex Sentences to Linked Propositions
In that way, we generate a semantic hierarchy of minimal propositions that leads to a novel representation of complex assertions that puts a semantic layer on top of the simplified sentences.
Context-Preserving Text Simplification
We present a context-preserving text simplification (TS) approach that recursively splits and rephrases complex English sentences into a semantic hierarchy of simplified sentences.
DisSim: A Discourse-Aware Syntactic Text Simplification Framework for English and German
We introduce DisSim, a discourse-aware sentence splitting framework for English and German whose goal is to transform syntactically complex sentences into an intermediate representation that presents a simple and more regular structure which is easier to process for downstream semantic applications.
DisSim: A Discourse-Aware Syntactic Text Simplification Frameworkfor English and German
We introduce DisSim, a discourse-aware sentence splitting framework for English and German whose goal is to transform syntactically complex sentences into an intermediate representation that presents a simple and more regular structure which is easier to process for downstream semantic applications.
Transforming Complex Sentences into a Semantic Hierarchy
We present an approach for recursively splitting and rephrasing complex English sentences into a novel semantic hierarchy of simplified sentences, with each of them presenting a more regular structure that may facilitate a wide variety of artificial intelligence tasks, such as machine translation (MT) or information extraction (IE).
Graphene: A Context-Preserving Open Information Extraction System
In that way, we preserve the context of the relational tuples extracted from a source sentence, generating a novel lightweight semantic representation for Open IE that enhances the expressiveness of the extracted propositions.
Graphene: Semantically-Linked Propositions in Open Information Extraction
We present an Open Information Extraction (IE) approach that uses a two-layered transformation stage consisting of a clausal disembedding layer and a phrasal disembedding layer, together with rhetorical relation identification.
A Survey on Open Information Extraction
We provide a detailed overview of the various approaches that were proposed to date to solve the task of Open Information Extraction.
