Named Entity Recognition over FBNER: A New Facebook Dataset in Turkish
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Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, we introduce a new Named Entity Recognition (NER) dataset of Facebook messages written in the Turkish language. We also employ a Conditional Random Fields based NER system to discover named entities from Facebook messages. Our system achieves an F1 score of 0.713 when training and test sets include Facebook posts. We also obtained an F1 score of 0.599 when the training set is from the news domain. A strength of this research is that it is one of the first studies in this field that focuses on NER over Turkish Facebook messages. This is because performing NER on user-generated content turns into a very challenging task since such informal contents are often noisy texts that have arammatical and spelling errors. © 2021 IEEE.
Açıklama
IEEE SMC Society; IEEE Turkey Section
2021 Innovations in Intelligent Systems and Applications Conference, ASYU 2021 -- 6 October 2021 through 8 October 2021 -- Elazig -- 174400
2021 Innovations in Intelligent Systems and Applications Conference, ASYU 2021 -- 6 October 2021 through 8 October 2021 -- Elazig -- 174400
Anahtar Kelimeler
conditional random fields, Facebook, named entity recognition
Kaynak
Proceedings - 2021 Innovations in Intelligent Systems and Applications Conference, ASYU 2021
