Recurrent neural networks for Turkish named entity recognition Özyinelemeli sinir aǧlariyla Türkçe varlik ismi tanima
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, İzmir, Türkiye, 2 - 05 Mayıs 2018, ss.1-4, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/siu.2018.8404788
- Basıldığı Şehir: İzmir
- Basıldığı Ülke: Türkiye
- Sayfa Sayıları: ss.1-4
- Anahtar Kelimeler: Named entity recognition, Natural language processing, Neural networks
- Boğaziçi Üniversitesi Adresli: Evet
Özet
In this work, we propose a neural network model for Turkish named entity recognition. Model creates a context vector for every position in the sentence by processing the words in forward and backward directions. This context vector is used to obtain a score vector for deciding whether there is an entity in that position or not. A conditional random field (CRF) model is employed to decide the final entity label. In our experiments using this model, performance results higher than the previous works in the literature were observed.