  In this paper, we present the first automatic lexical simplification system
for the Turkish language. Recent text simplification efforts rely on manually
crafted simplified corpora and comprehensive NLP tools that can analyse the
target text both in word and sentence levels. Turkish is a morphologically rich
agglutinative language that requires unique considerations such as the proper
handling of inflectional cases. Being a low-resource language in terms of
available resources and industrial-strength tools, it makes the text
simplification task harder to approach. We present a new text simplification
pipeline based on pretrained representation model BERT together with
morphological features to generate grammatically correct and semantically
appropriate word-level simplifications.
