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Yazar: Ehsani, Razieh × Konu: Natural language processing systems ×

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Listeleniyor 1 - 4 / 4
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    Vikipedi ve Vikisözlük'ten Hypernym çıkarma
    (IEEE, 2017-06-27) Şaşmaz, Emre; Ehsani, Razieh; Yıldız, Olcay Taner
    Doğal dil işleme alanında kullanılan önemli yapılardan bir tanesi WordNet gibi büyük ölçekli sözlüklerdir. WordNet; eşanlamlı, zıt anlamlı gibi anlamsal ilişkileri de içeren kapsamlı bir sözlüktür. Bu bildiride, WordNet’in önemli bir parçası olan Hypernym-Hyponym ilişkisini çıkarmaya çalıştık. Bu amaca ulaşmak için, Vikipedi, Türkçe Sözlük ve Vikisözlük kaynaklarını kullandık. Sonlu Durum Makinelerinden ürettiğimiz kurallarla Hypernym-Hyponym ilişkilerini çıkardık.
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    MorAz: An open-source morphological analyzer for Azerbaijani Turkish
    (Association for Computational Linguistics (ACL), 2018) Özenç, Berke; Ehsani, Razieh; Solak, Ercan
    MorAz 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.
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    Chunking in Turkish with conditional random fields
    (Springer-Verlag, 2015-04-14) Yıldız, Olcay Taner; Solak, Ercan; Ehsani, Razieh; Görgün, Onur
    In 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.
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    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.