Ara
Toplam kayıt 5, listelenen: 1-5
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 ...
A multilayer annotated corpus for Turkish
(IEEE, 2018-06-06)
In this paper, we present the first multilayer annotated corpus for Turkish, which is a low-resourced agglutinative language. Our dataset consists of 9,600 sentences translated from the Penn Treebank Corpus. Annotated ...
AnlamVer: Semantic model evaluation dataset for Turkish - word similarity and relatedness
(Association for Computational Linguistics (ACL), 2018-08-26)
In this paper, we present AnlamVer, which is a semantic model evaluation dataset for Turkish designed to evaluate word similarity and word relatedness tasks while discriminating those two relations from each other. Our ...