Search Results for author: Bilge Nas Arıcan

Found 6 papers, 1 papers with code

Building the Turkish FrameNet

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.

Creating Domain Dependent Turkish WordNet and SentiNet

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.

LEMMA Sentiment Analysis

English-Turkish Parallel Semantic Annotation of Penn-Treebank

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.

From Constituency to UD-Style Dependency: Building the First Conversion Tool of Turkish

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.

BIG-bench Machine Learning

Cannot find the paper you are looking for? You can Submit a new open access paper.