Özlem Ergelen


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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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English-Turkish Parallel Semantic Annotation of Penn-Treebank
Bilge Nas Arıcan | Özge Bakay | Begüm Avar | Olcay Taner Yıldız | Özlem Ergelen
Proceedings of the 10th Global Wordnet Conference

This paper reports our efforts in constructing a sense-labeled English-Turkish parallel corpus using the traditional method of manual tagging. We tagged a pre-built parallel treebank which was translated from the Penn Treebank corpus. This approach allowed us to generate a resource combining syntactic and semantic information. We provide statistics about the corpus itself as well as information regarding its development process.