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Transforming Complex Sentences into a Semantic Hierarchy
Type
conference paper
Date Issued
2019-07
Author(s)
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 two-layered 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.
Language
English
HSG Classification
contribution to scientific community
Book title
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Publisher
Association for Computational Linguistics
Publisher place
Florence, Italy
Start page
3415
End page
3427
Event Title
57th Annual Meeting of the Association for Computational Linguistics (ACL)
Event Location
Florence, Italy
Event Date
28.07.2019 - 02.08.2019
Official URL
Subject(s)
Division(s)
Eprints ID
258033
File(s)