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RTE: A Tool for Annotating Relation Triplets from Text

Authors :
Mullick, Ankan
Bera, Animesh
Nayak, Tapas
Publication Year :
2021

Abstract

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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2108.08184
Document Type :
Working Paper