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Toplam kayıt 7, listelenen: 1-7
Shallow parsing in Turkish
(IEEE, 2017)
In this study, shallow parsing is applied on Turkish sentences. These sentences are used to train and test the per-formances of various learning algorithms with various features specified for shallow parsing in Turkish.
All-words word sense disambiguation for Turkish
(IEEE, 2017)
Identifying the sense of a word within a context is a challenging problem and has many applications in natural language processing. This assignment problem is called word sense disambiguation(WSD). Many papers in the ...
An open, extendible, and fast Turkish morphological analyzer
(Incoma Ltd, 2019-09)
In this paper, we present a two-level morphological analyzer for Turkish which consists of five main components: finite state transducer, rule engine for suffixation, lexicon, trie data structure, and LRU cache. We use ...
English-Turkish parallel semantic annotation of Penn-Treebank
(Oficyna Wydawnicza Politechniki Wroclawskiej, 2020)
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 ...
Comparing sense categorization between English propbank and english wordnet
(Oficyna Wydawnicza Politechniki Wroclawskiej, 2020)
Given the fact that verbs play a crucial role in language comprehension, this paper presents a study which compares the verb senses in English PropBank with the ones in English WordNet through manual tagging. After analyzing ...
A tree-based approach for English-to-Turkish translation
(Tubitak Scientific & Technical Research Council Turkey, 2019)
In this paper, we present our English-to-Turkish translation methodology, which adopts a tree-based approach. Our approach relies on tree analysis and the application of structural modification rules to get the target side ...
A new approach for named entity recognition
(IEEE, 2017)
Many sentences create certain impressions on people. These impressions help the reader to have an insight about the sentence via some entities. In NLP, this process corresponds to Named Entity Recognition (NER). NLP ...