  In this work, we present a Web-based annotation tool `Relation Triplets
Extractor' \footnote{https://abera87.github.io/annotate/} (RTE) for annotating
relation triplets from the text. Relation extraction is an important task for
extracting structured information about real-world entities from the
unstructured text available on the Web. In relation extraction, we focus on
binary relation that refers to relations between two entities. Recently, many
supervised models are proposed to solve this task, but they mostly use noisy
training data obtained using the distant supervision method. In many cases,
evaluation of the models is also done based on a noisy test dataset. The lack
of annotated clean dataset is a key challenge in this area of research. In this
work, we built a web-based tool where researchers can annotate datasets for
relation extraction on their own very easily. We use a server-less architecture
for this tool, and the entire annotation operation is processed using
client-side code. Thus it does not suffer from any network latency, and the
privacy of the user's data is also maintained. We hope that this tool will be
beneficial for the researchers to advance the field of relation extraction.
