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Yayın Visual modeling of Turkish morphology(European Language Resources Association (ELRA), 2020-05-16) Özenç, Berke; Solak, ErcanIn this paper, we describe the steps in a visual modeling of Turkish morphology using diagramming tools. We aimed to make modeling easier and more maintainable while automating much of the code generation. We released the resulting analyzer, MorTur, and the diagram conversion tool, DiaMor as free, open-source utilities. MorTur analyzer is also publicly available on its web page as a web service. MorTur and DiaMor are part of our ongoing efforts in building a set of natural language processing tools for Turkic languages under a consistent framework.Yayın Kural bazlı otomatik haber etiketleme(IEEE, 2017-06-27) Özenç, Berke; Solak, ErcanBu çalışmada , genel ağ kaynaklarından haber toplayan ve topladığı bu haberleri otomatik olarak etiketleyen kural tabanlı bir uygulama yapılmıştır. Çalışmanın alt amacı hangi özelliklerin etiket belirleme işine daha uygun olduğunu ölçmektir. Elle etiketlenmiş 100 haber üzerinde her bir kuralın başarısı oranı ölçülmüştür.Yayın Bilingual software requirements tracing using vector space model(SciTePress, 2014) Yıldız, Olcay Taner; Okutan, Ahmet; Solak, ErcanIn the software engineering world, creating and maintaining relationships between byproducts generated during the software lifecycle is crucial. A typical relation is the one that exists between an item in the requirements document and a block in the subsequent system design, i.e. class in the source code. In many software engineering projects, the requirement documentation is prepared in the language of the developers, whereas developers prefer to use the English language in the software development process. In this paper, we use the vector space model to extract traceability links between the requirements written in one language (Turkish) and the implementations of classes in another language (English). The experiments show that, by using a generic translator such as Google translate, we can obtain promising results, which can also be improved by using comment info in the source code.Yayın MorAz: An open-source morphological analyzer for Azerbaijani Turkish(Association for Computational Linguistics (ACL), 2018) Özenç, Berke; Ehsani, Razieh; Solak, ErcanMorAz is an open-source morphological analyzer for Azerbaijani Turkish. The analyzer is available through both as a website for interactive exploration and as a RESTful web service for integration into a natural language processing pipeline. MorAz implements the morphology of Azerbaijani Turkish following a two-level approach using Helsinki finite-state transducer and wraps the analyzer with python scripts in a Django instance.Yayın Kaotik kriptografinin çilesi(IEEE, 2013-06-13) Solak, ErcanSon yirmi yıldır araştırılan bir konu olmasına rağmen, kaotik kriptografi ana akım kriptografi literatüründe yer almıyor. Bu makalede, bu ayrımın nedenleri üzerinde durulmuştur.Yayın Constructing a Turkish constituency parse treeBank(Springer Verlag, 2016) Yıldız, Olcay Taner; Solak, Ercan; Çandır, Şemsinur; Ehsani, Razieh; Görgün, OnurIn this paper, we describe our initial efforts for creating a Turkish constituency parse treebank by utilizing the English Penn Treebank. We employ a semiautomated approach for annotation. In our previouswork [18], the English parse trees were manually translated to Turkish. In this paper, the words are semi-automatically annotated morphologically. As a second step, a rule-based approach is used for refining the parse trees based on the morphological analyses of the words. We generated Turkish phrase structure trees for 5143 sentences from Penn Treebank that contain fewer than 15 tokens. The annotated corpus can be used in statistical natural language processing studies for developing tools such as constituency parsers and statistical machine translation systems for Turkish.Yayın An experimental evaluation of prior polarities in sentiment lexicons(IEEE, 2017) Kanburoğlu, Ali Buğra; Solak, ErcanWe present the results of an experiment to assess the validity of prior polarities available in sentiment lexicons. We designed a ranking task that was elicited through pairwise comparisons and compared the results to those predicted by two popular sentiment lexicons. We find that the experiment results show a moderate level of agreement between the lexicons and human judgments.Yayın Chunking in Turkish with conditional random fields(Springer-Verlag, 2015-04-14) Yıldız, Olcay Taner; Solak, Ercan; Ehsani, Razieh; Görgün, OnurIn this paper, we report our work on chunking in Turkish. We used the data that we generated by manually translating a subset of the Penn Treebank. We exploited the already available tags in the trees to automatically identify and label chunks in their Turkish translations. We used conditional random fields (CRF) to train a model over the annotated data. We report our results on different levels of chunk resolution.Yayın A FST description of noun and verb morphology of Azarbaijani Turkish(Association for Computational Linguistics (ACL), 2021) Ehsani, Razieh; Özenç, Berke; Solak, Ercan; Drewes F.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 as optional paths on the FST. We collapse adjective and noun categories in a single nominal category as they behave similarly as far as their paradigms are concerned. Thus, we defer a more precise identification of POS to further down the NLP pipeline.Yayın Constructing a Turkish-English parallel treebank(Association for Computational Linguistics (ACL), 2014) Yıldız, Olcay Taner; Solak, Ercan; Görgün, Onur; Ehsani, RaziehIn this paper, we report our preliminary efforts in building an English-Turkish parallel treebank corpus for statistical machine translation. In the corpus, we manually generated parallel trees for about 5,000 sentences from Penn Treebank. English sentences in our set have a maximum of 15 tokens, including punctuation. We constrained the translated trees to the reordering of the children and the replacement of the leaf nodes with appropriate glosses. We also report the tools that we built and used in our tree translation task.
