Top 5 Tools to Use for Natural Language Annotation

Here are the 5 tools that are useful for natural language annotation in 2023

Machine learning (ML) is a potent natural language processing (NLP). With the use of this method, machines can converse in human language. This technology is used in several widely used types of AI. For instance, these technologies were used to develop virtual assistants like Siri and Alexa.

The term "natural language understanding" (NLU) refers to a group of various methods. NLU concentrates on employing computers to decipher the meaning of written language. As a result, people can converse naturally with computers. Additionally, it enables users to convert unstructured text into structured data. Product reviews, tweets, and support tickets fall under this category. NLU and NLP are effective, time-saving techniques. However, you must begin with high-quality data to produce useful models. Large volumes of text were manually tagged to produce this data. Data scientists train the computer to classify text in this manner. This approach takes a long time because it calls for applying tags after going through each example.

1. Text Engineering General Architecture (GATE)

GATE has been a free, open-source project for fifteen years. The project has produced a variety of potent language-processing applications throughout this period. These tools support a variety of tasks, including benchmarking, processing, and labeling. Many of the engineering difficulties involved in developing a language processing workflow are intended to be eliminated by GATE. Desktop Java program GATE Developer is their main offering. They furthermore provide a web-based solution called GATE Cloud.

2. BRAT

Another free tool for tagging data is BRAT (Browser-Based Rapid Annotation Tool). It offers a text annotation experience that is browser-based. It makes several NLP annotation jobs easier. Brat is a well-liked tool with a strong support network for this work. Additionally, brat offers connectivity with outside sites like Wikipedia. With this technology, businesses may build up servers where many people can add annotations. However, some server administration and technical expertise are needed for this.

3. Doccano

A web-based annotation tool is called Doccano. It offers a beautiful user interface for a few crucial annotation tasks. It is hosted on GitHub and is open-source. It is available for free download and free use on any server. Compared to programs like Brat and WebAnno, it is less flexible. Additionally, it only supports more difficult annotation jobs. Duccano does not support relationships between words and nested classes. Even yet, most production models cannot exploit this kind of information. Docanno makes up for its lack of customization with its simplicity. Using a straightforward display, annotators can choose text and select an annotation from a list of keyboard shortcuts.

4. SwivlStudio

SwivlStudio is one of the most user-friendly tools for labeling text for ML training. The most labor-intensive step in ML is data labeling. Allowing end users to participate in training might be challenging due to several systems. Swivl offers an integrated solution that streamlines this procedure, however. The whole workflow, from data tagging through customer involvement, is integrated.

Swivl also has a user-friendly user interface for people without programming skills. Users may train models using a straightforward point-and-click interface. Tools for guided data tagging offer recommendations to lighten the annotator's burden. The emphasis on human-in-the-loop (HitL) design is the other characteristic that sets swivl apart. This tactic combines the positive aspects of both human and artificial intelligence. Swivl can achieve far higher accuracy by continuously updating the ML model with user feedback. This idea serves as the foundation of swivlStudio. By doing this, models are made to be flexible and improve over time. Swivl is simple for businesses to use thanks to its integrated workflow. They come with a user-friendly solution that enables companies to apply NLP for client success. A sophisticated option for companies of any size is swivlStudio. As your business expands, these technologies will significantly reduce the time spent on customer support.

5. Bella

Bella is a JavaScript-based NLP tagging tool. It offers a straightforward online interface for labeling text data. However, it is intended for programmers that feel at ease with command-line programs, Node Package Manager (NPM), and Docker. It is intended to assist data scientists in retraining NLP models. To handle NLP datasets, it also offers a GUI and a database.