TY  - JOUR
TI  - Neural relation extraction: a review
AB  - Neural relation extraction discovers semantic relations between entities from unstructured text using deep
learning methods. In this study, we make a clear categorization of the existing relation extraction methods in terms
of data expressiveness and data supervision, and present a comprehensive and comparative review. We describe the
evaluation methodologies and the datasets used for model assessment. We explicitly state the common challenges in
relation extraction task and point out the potential of the pretrained models to solve them. Accordingly, we investigate
additional research directions and improvement ideas in this field.
AU  - SARPÜN, İsmail Hakkı
AU  - Inal, Aysun
AU  - AYDAR, MEHMET
AU  - Özbay, Furkan
AU  - Bozal, Ozge
DO  - 10.3906/elk-2005-119
PY  - 2021
JO  - Turkish Journal of Electrical Engineering and Computer Sciences
VL  - 8
IS  - 2
SN  - 1300-0632
SP  - 1029
EP  - 1043
DB  - TRDizin
UR  - http://search/yayin/detay/514960
ER  -