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

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	From complex sentences to a formal semantic representation using syntactic text simplification and open information extractionby Christina Niklaus.
作者:	Niklaus, Christina.
出版者:	Wiesbaden :Springer Fachmedien Wiesbaden :2022.
面頁冊數:	xli, 318 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Natural language processing (Computer science)
電子資源:	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
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