Papers by Nikola Zdravkovic
The Meaning of Meaning: Leech's Seven Types of Meaning in Comparison to Palmer's and Lyons' Approaches, 2018
Grammatische Angaben: Verben – Ein Vergleich zwischen E-VALBU und LGWDaF hinsichtlich der Verbvalenz, 2018
Drafts by Nikola Zdravkovic
Modern Serbian Lexicography: Early Beginnings and Contemporary Digitization, 2018
Thesis Chapters by Nikola Zdravkovic
Criteria and Gold Standards for the Automatic Identification of Multiword Expressions: Lexicographic Perspective, 2020
The present thesis aims to provide an insight from a lexicographic perspective into the problemat... more The present thesis aims to provide an insight from a lexicographic perspective into the problematic field of research concerned with multiword expressions, criteria according to which they are identified and classified, the identification process thereof itself as well as with the state of the art of gold standards used for their automatic identification. After the introductory part, an explanation as to what lexicography is and what constitutes the lexicographic approach shall follow along with the theoretical background of multiword expressions. An overview of the criteria for the classification and identification of multiword expressions accompanied by the set thereof established by the author of the present thesis is the middle part of the work. Finally, after describing some of the current gold standards for the automatic identification of MWEs, PARSEME’s corpora from three different languages are analyzed and evaluated which leads to the conclusion where a summary of everything done is provided together with certain suggestions for future work on the topic.
Keywords: Multiword Expression, Lexicography, NLP, Gold Standard, Automatic Identification, PARSEME
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Papers by Nikola Zdravkovic
Drafts by Nikola Zdravkovic
Thesis Chapters by Nikola Zdravkovic
Keywords: Multiword Expression, Lexicography, NLP, Gold Standard, Automatic Identification, PARSEME
Keywords: Multiword Expression, Lexicography, NLP, Gold Standard, Automatic Identification, PARSEME