國立高雄大學圖資館 |

From complex sentences to a formal semantic representation using syntactic text simplification and open information extraction

Record Type:	Electronic resources : Monograph/item
Title/Author:	From complex sentences to a formal semantic representation using syntactic text simplification and open information extractionby Christina Niklaus.
Author:	Niklaus, Christina.
Published:	Wiesbaden :Springer Fachmedien Wiesbaden :2022.
Description:	xli, 318 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Natural language processing (Computer science)
Online resource:	https://doi.org/10.1007/978-3-658-38697-9
ISBN:	9783658386979$q(electronic bk.)

From complex sentences to a formal semantic representation using syntactic text simplification and open information extraction
Niklaus, Christina.

From complex sentences to a formal semantic representation using syntactic text simplification and open information extraction[electronic resource] /by Christina Niklaus. - Wiesbaden :Springer Fachmedien Wiesbaden :2022. - xli, 318 p. :ill. (some col.), digital ;24 cm.

Background -- Discourse-Aware Sentence Splitting -- Open Information Extraction -- Evaluation -- Conclusion.

This work presents a discourse-aware Text Simplification approach that splits and rephrases complex English sentences within the semantic context in which they occur. Based on a linguistically grounded transformation stage, complex sentences are transformed into shorter utterances with a simple canonical structure that can be easily analyzed by downstream applications. To avoid breaking down the input into a disjointed sequence of statements that is difficult to interpret, the author incorporates the semantic context between the split propositions in the form of hierarchical structures and semantic relationships, thus generating a novel representation of complex assertions that puts a semantic layer on top of the simplified sentences. In a second step, she leverages the semantic hierarchy of minimal propositions to improve the performance of Open IE frameworks. She shows that such systems benefit in two dimensions. First, the canonical structure of the simplified sentences facilitates the extraction of relational tuples, leading to an improved precision and recall of the extracted relations. Second, the semantic hierarchy can be leveraged to enrich the output of existing Open IE approaches with additional meta-information, resulting in a novel lightweight semantic representation for complex text data in the form of normalized and context-preserving relational tuples. About the author Christina Niklaus is an Assistant Professor in Computer Science at the University of St.Gallen with a focus on Data Science and NLP.

ISBN: 9783658386979$q(electronic bk.)

Standard No.: 10.1007/978-3-658-38697-9doiSubjects--Topical Terms:

200539
Natural language processing (Computer science)

LC Class. No.: QA76.9.N38 / N55 2022

Dewey Class. No.: 006.35

From complex sentences to a formal semantic representation using syntactic text simplification and open information extraction
LDR:02678nmm a2200313 a 4500 001 629095
003 DE-He213
005 20220829134616.0
007 cr nn 008maaau
008 230224s2022 gw s 0 eng d
020 $a 9783658386979$q(electronic bk.)
020 $a 9783658386962$q(paper)
024 7 $a 10.1007/978-3-658-38697-9 $2 doi
035 $a 978-3-658-38697-9
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.N38 $b N55 2022
072 7 $a CFX $2 bicssc
072 7 $a LAN009000 $2 bisacsh
072 7 $a CFX $2 thema
082 0 4 $a 006.35 $2 23
090 $a QA76.9.N38 $b N692 2022
100 1 $a Niklaus, Christina. $3 933646
245 1 0 $a From complex sentences to a formal semantic representation using syntactic text simplification and open information extraction $h [electronic resource] / $c by Christina Niklaus.
260 $a Wiesbaden : $b Springer Fachmedien Wiesbaden : $b Imprint: Springer Vieweg, $c 2022.
300 $a xli, 318 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Background -- Discourse-Aware Sentence Splitting -- Open Information Extraction -- Evaluation -- Conclusion.
520 $a This work presents a discourse-aware Text Simplification approach that splits and rephrases complex English sentences within the semantic context in which they occur. Based on a linguistically grounded transformation stage, complex sentences are transformed into shorter utterances with a simple canonical structure that can be easily analyzed by downstream applications. To avoid breaking down the input into a disjointed sequence of statements that is difficult to interpret, the author incorporates the semantic context between the split propositions in the form of hierarchical structures and semantic relationships, thus generating a novel representation of complex assertions that puts a semantic layer on top of the simplified sentences. In a second step, she leverages the semantic hierarchy of minimal propositions to improve the performance of Open IE frameworks. She shows that such systems benefit in two dimensions. First, the canonical structure of the simplified sentences facilitates the extraction of relational tuples, leading to an improved precision and recall of the extracted relations. Second, the semantic hierarchy can be leveraged to enrich the output of existing Open IE approaches with additional meta-information, resulting in a novel lightweight semantic representation for complex text data in the form of normalized and context-preserving relational tuples. About the author Christina Niklaus is an Assistant Professor in Computer Science at the University of St.Gallen with a focus on Data Science and NLP.
650 0 $a Natural language processing (Computer science) $3 200539
650 0 $a Text processing (Computer science) $3 210527
650 0 $a Computational linguistics. $3 181250
650 1 4 $a Computational Linguistics. $3 274669
650 2 4 $a Natural Language Processing (NLP) $3 826373
650 2 4 $a Programming Language. $3 913494
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-658-38697-9
950 $a Education (SpringerNature-41171)