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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM14651
Volume:
6 |
6 |
Jun 2022
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This paper presents the importance and use of text annotation in NLP models and reviews BRAT – an NLP-assisted text annotation tool and other powerful and modern methods. BRAT is an NLP-based tool for text annotation (annotation: making notes, adding comments to a text in order to give an explanation or opinion to the source article). It is used for high-quality structured annotation for various NLP activities and focuses on increasing annotator productivity using NLP techniques. Annotation teaches NLP models how to identify parts of speech, real-world objects (named entities such as a person, location, place), and key phrases within a text. NLP algorithms are trained using large, annotated text datasets and annotation is the backbone of services like automatic speech recognition, chatbots, and sentimental analysis.
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Publication Date
6/15/2022
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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