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  Constructing Lexicons of Relational Phrases

Grycner, A. (2017). Constructing Lexicons of Relational Phrases. PhD Thesis, Universität des Saarlandes, Saarbrücken.

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Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-933B-1 Versions-Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-933C-0
Genre: Hochschulschrift

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http://scidok.sulb.uni-saarland.de/volltexte/2017/6910/ (beliebiger Volltext)
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http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=de (Verlagsvertrag)
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 Urheber:
Grycner, Adam1, 2, Autor           
Weikum, Gerhard1, Ratgeber           
Klakow, Dietrich3, Gutachter
Ponzetto, Simone Paolo3, Gutachter
Affiliations:
1Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              
2International Max Planck Research School, MPI for Informatics, Max Planck Society, Campus E1 4, 66123 Saarbrücken, DE, ou_1116551              
3External Organizations, ou_persistent22              

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Schlagwörter: -
 Zusammenfassung: Knowledge Bases are one of the key components of Natural Language Understanding systems. For example, DBpedia, YAGO, and Wikidata capture and organize knowledge about named entities and relations between them, which is often crucial for tasks like Question Answering and Named Entity Disambiguation. While Knowledge Bases have good coverage of prominent entities, they are often limited with respect to relations. The goal of this thesis is to bridge this gap and automatically create lexicons of textual representations of relations, namely relational phrases. The lexicons should contain information about paraphrases, hierarchy, as well as semantic types of arguments of relational phrases. The thesis makes three main contributions. The first contribution addresses disambiguating relational phrases by aligning them with the WordNet dictionary. Moreover, the alignment allows imposing the WordNet hierarchy on the relational phrases. The second contribution proposes a method for graph construction of relations using Probabilistic Graphical Models. In addition, we apply this model to relation paraphrasing. The third contribution presents a method for constructing a lexicon of relational paraphrases with fine-grained semantic typing of arguments. This method is based on information from a multilingual parallel corpus.

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Sprache(n): eng - English
 Datum: 2017-06-2820172017
 Publikationsstatus: Erschienen
 Seiten: 125 p.
 Ort, Verlag, Ausgabe: Saarbrücken : Universität des Saarlandes
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: BibTex Citekey: Grynerphd17
URN: urn:nbn:de:bsz:291-scidok-69101
 Art des Abschluß: Doktorarbeit

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