Özge Sevgili Ergüven

Name:	Özge Sevgili Ergüven
Position:	PhD Student
Email:	oezge.sevgili.ergueven@studium.uni-hamburg.de
Office:	F-407
Address:	Informatikum Vogt-Kölln-Straße 30 22527 Hamburg

I am a Ph.D. Student at the language technology group, under the supervision of Prof. Chris Biemann. I am a scholarship holder supported by DAAD. I am currently working on Entity Linking. My main research areas are representation learning, entity linking and disambiguation, and word sense disambiguation. I am also interested in pun detection/interpretation.

Publications

Sevgili, Ö., Shelmanov, A., Arkhipov, M., Panchenko, A., Biemann, C. (2022): Neural entity linking: A survey of models based on deep learning, Semantic Web Journal, vol. 13, no. 3, pp. 527-570, IOS Press (2022), doi:10.3233/SW-222986. (link)
Feng, J., Sevgili, Ö., Remus, S., Ruppert, E., Biemann, C. (2020): Supervised Pun Detection and Location with Feature Engineering and Logistic Regression. Proceedings of the 5th SwissText & 16th KONVENS Joint Conference 2020, Zurich, Switzerland. (pdf)
Sevgili, Ö., Panchenko, A., Biemann, C. (2019): Improving Neural Entity Disambiguation with Graph Embeddings. Proceedings of the ACL 2019 Student Research Workshop, Florence, Italy. (pdf)
Sezerer, E., Polatbilek, O., Sevgili, Ö., Tekir, S., (2018): Gender Prediction From Tweets With Convolutional Neural Networks: Notebook for PAN at CLEF 2018. Proceedings of the Ninth International Conference of the CLEF Association (CLEF 2018), Avignon, France.
Sevgili, Ö., Ghotbi, N., Tekir, S., (2017): N-hance at semeval-2017 task 7: A computational approach using word association for puns. Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), Vancouver, Canada.

Özge Sevgili Ergüven

Publications

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