no code implementations • EACL (GWC) 2021 • Büşra Marşan, Neslihan Kara, Merve Özçelik, Bilge Nas Arıcan, Neslihan Cesur, Aslı Kuzgun, Ezgi Sanıyar, Oğuzhan Kuyrukçu, Olcay Taner Yildiz
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.
no code implementations • EACL (GWC) 2021 • Merve Özçelik, Bilge Nas Arıcan, Özge Bakay, Elif Sarmış, Özlem Ergelen, Nilgün Güler Bayezit, Olcay Taner Yildiz
Dictionary-based methods in sentiment analysis have received scholarly attention recently, the most comprehensive examples of which can be found in English.
5 code implementations • EACL (GWC) 2021 • Özge Bakay, Özlem Ergelen, Elif Sarmış, Selin Yıldırım, Bilge Nas Arıcan, Atilla Kocabalcıoğlu, Merve Özçelik, Ezgi Sanıyar, Oğuzhan Kuyrukçu, Begüm Avar, Olcay Taner Yildiz
Currently, there are two available wordnets for Turkish: TR-wordnet of BalkaNet and KeNet.
no code implementations • EACL (GWC) 2021 • Bilge Nas Arıcan, Merve Özçelik, Deniz Baran Aslan, Elif Sarmış, Selen Parlar, Olcay Taner Yildiz
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.
no code implementations • GWC 2019 • Bilge Nas Arıcan, Özge Bakay, Begüm Avar, Olcay Taner Yildiz, Özlem Ergelen
This paper reports our efforts in constructing a sense-labeled English-Turkish parallel corpus using the traditional method of manual tagging.
no code implementations • RANLP 2021 • Aslı Kuzgun, Oğuz Kerem Yıldız, Neslihan Cesur, Büşra Marşan, Arife Betül Yenice, Ezgi Sanıyar, Oguzhan Kuyrukçu, Bilge Nas Arıcan, Olcay Taner Yildiz
Within the scope of this project, these Turkish phrase structure trees were automatically converted into UD-style dependency structures, using both a rule-based algorithm and a machine learning algorithm specific to the requirements of the Turkish language.