Transforming Complex Sentences into a Semantic Hierarchy

Christina Niklaus, Matthias Cetto, Andre Freitas, Siegfried Handschuh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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). Using a set of hand-crafted transformation rules, input sentences are recursively transformed into a twolayered hierarchical representation in the form of core sentences and accompanying contexts that are linked via rhetorical relations. In this way, the semantic relationship of the decomposed constituents is preserved in the output, maintaining its interpretability for downstream applications. Both a thorough manual analysis and automatic evaluation across three datasets from two different domains demonstrate that the proposed syntactic simplification approach outperforms the state of the art in structural text simplification. Moreover, an extrinsic evaluation shows that when applying our framework as a preprocessing step the performance of state-of-the-art Open IE systems can be improved by up to 346% in precision and 52% in recall. To enable reproducible research, all code is provided online.
Original languageEnglish
Title of host publicationProceedings of the 57th Annual Meeting of the Association for Computational Linguistics
DOIs
Publication statusPublished - Jul 2019
Event57th Annual Meeting of the Association for Computational Linguistics -
Duration: 28 Jul 20192 Aug 2019

Conference

Conference57th Annual Meeting of the Association for Computational Linguistics
Period28/07/192/08/19

Fingerprint

Dive into the research topics of 'Transforming Complex Sentences into a Semantic Hierarchy'. Together they form a unique fingerprint.

Cite this