Ara
Toplam kayıt 6, listelenen: 1-6
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 ...
Automatic propbank generation for Turkish
(Incoma Ltd, 2019-09)
Semantic role labeling (SRL) is an important task for understanding natural languages, where the objective is to analyse propositions expressed by the verb and to identify each word that bears a semantic role. It provides ...
Creating a syntactically felicitous constituency treebank for Turkish
(Institute of Electrical and Electronics Engineers Inc., 2020-10-15)
In this study, Bakay et. al [1] and Yildiz et. al.'s [2] work on Turkish constituency treebanks were developed further. Compared to the previous work, the most prominent feature of this study is the fact that every annotation ...
A FST description of noun and verb morphology of Azarbaijani Turkish
(Association for Computational Linguistics (ACL), 2021)
We give a FST description of nominal and finite verb morphology of Azarbaijani Turkish. We use a hybrid approach where nominal inflection is expressed as a slot-based paradigm and major parts of verb inflection are expressed ...
Problems caused by semantic drift in WordNet synset construction
(Institute of Electrical and Electronics Engineers Inc., 2019-09)
In this study, we summarize the semantic drift problem that occur in specific synsets of KeNet, a Turkish WordNet, which is caused by mis-merging of semantically-related lexical items, morphological markings and false part ...
Integrating Turkish Wordnet KeNet to Princeton WordNet: The case of one-to-many correspondences
(Institute of Electrical and Electronics Engineers Inc., 2019-10)
In this paper, we introduce a novel approach of forming interlingual relations between multilingual wordnets. We have mapped Turkish senses in KeNet with their corresponding senses in Princeton WordNet by drawing one-To-many ...