Merve Özçelik

Also published as: Merve Ozcelik


2022

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Morpholex Turkish: A Morphological Lexicon for Turkish
Bilge Arican | Aslı Kuzgun | Büşra Marşan | Deniz Baran Aslan | Ezgi Saniyar | Neslihan Cesur | Neslihan Kara | Oguzhan Kuyrukcu | Merve Ozcelik | Arife Betul Yenice | Merve Dogan | Ceren Oksal | Gökhan Ercan | Olcay Taner Yıldız
Proceedings of Globalex Workshop on Linked Lexicography within the 13th Language Resources and Evaluation Conference

MorphoLex is a study in which root, prefix and suffixes of words are analyzed. With MorphoLex, many words can be analyzed according to certain rules and a useful database can be created. Due to the fact that Turkish is an agglutinative language and the richness of its language structure, it offers different analyzes and results from previous studies in MorphoLex. In this study, we revealed the process of creating a database with 48,472 words and the results of the differences in language structure.

2021

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Building the Turkish FrameNet
Büşra Marşan | Neslihan Kara | Merve Özçelik | Bilge Nas Arıcan | Neslihan Cesur | Aslı Kuzgun | Ezgi Sanıyar | Oğuzhan Kuyrukçu | Olcay Taner Yildiz
Proceedings of the 11th Global Wordnet Conference

FrameNet (Lowe, 1997; Baker et al., 1998; Fillmore and Atkins, 1998; Johnson et al., 2001) is a computational lexicography project that aims to offer insight into the semantic relationships between predicate and arguments. Having uses in many NLP applications, FrameNet has proven itself as a valuable resource. The main goal of this study is laying the foundation for building a comprehensive and cohesive Turkish FrameNet that is compatible with other resources like PropBank (Kara et al., 2020) or WordNet (Bakay et al., 2019; Ehsani, 2018; Ehsani et al., 2018; Parlar et al., 2019; Bakay et al., 2020) in the Turkish language.

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HisNet: A Polarity Lexicon based on WordNet for Emotion Analysis
Merve Özçelik | Bilge Nas Arıcan | Özge Bakay | Elif Sarmış | Özlem Ergelen | Nilgün Güler Bayezit | Olcay Taner Yıldız
Proceedings of the 11th Global Wordnet Conference

Dictionary-based methods in sentiment analysis have received scholarly attention recently, the most comprehensive examples of which can be found in English. However, many other languages lack polarity dictionaries, or the existing ones are small in size as in the case of SentiTurkNet, the first and only polarity dictionary in Turkish. Thus, this study aims to extend the content of SentiTurkNet by comparing the two available WordNets in Turkish, namely KeNet and TR-wordnet of BalkaNet. To this end, a current Turkish polarity dictionary has been created relying on 76,825 synsets matching KeNet, where each synset has been annotated with three polarity labels, which are positive, negative and neutral. Meanwhile, the comparison of KeNet and TR-wordnet of BalkaNet has revealed their weaknesses such as the repetition of the same senses, lack of necessary merges of the items belonging to the same synset and the presence of redundant narrower versions of synsets, which are discussed in light of their potential to the improvement of the current lexical databases of Turkish.

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Turkish WordNet KeNet
Özge Bakay | Özlem Ergelen | Elif Sarmış | Selin Yıldırım | Bilge Nas Arıcan | Atilla Kocabalcıoğlu | Merve Özçelik | Ezgi Sanıyar | Oğuzhan Kuyrukçu | Begüm Avar | Olcay Taner Yıldız
Proceedings of the 11th Global Wordnet Conference

Currently, there are two available wordnets for Turkish: TR-wordnet of BalkaNet and KeNet. As the more comprehensive wordnet for Turkish, KeNet includes 76,757 synsets. KeNet has both intralingual semantic relations and is linked to PWN through interlingual relations. In this paper, we present the procedure adopted in creating KeNet, give details about our approach in annotating semantic relations such as hypernymy and discuss the language-specific problems encountered in these processes.

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Creating Domain Dependent Turkish WordNet and SentiNet
Bilge Nas Arıcan | Merve Özçelik | Deniz Baran Aslan | Elif Sarmış | Selen Parlar | Olcay Taner Yıldız
Proceedings of the 11th Global Wordnet Conference

A WordNet is a thesaurus that has a structured list of words organized depending on their meanings. WordNet represents word senses, all meanings a single lemma may have, the relations between these senses, and their definitions. Another study within the domain of Natural Language Processing is sentiment analysis. With sentiment analysis, data sets can be scored according to the emotion they contain. In the sentiment analysis we did with the data we received on the Tourism WordNet, we performed a domain-specific sentiment analysis study by annotating the data. In this paper, we propose a method to facilitate Natural Language Processing tasks such as sentiment analysis performed in specific domains via creating a specific-domain subset of an original Turkish dictionary. As the preliminary study, we have created a WordNet for the tourism domain with 14,000 words and validated it on simple tasks.