Corgi

Speed up your labelling efforts and ensure labelling uniformity

About Corgi

Many organisations are sitting on a repository of text documents. However, organisations are unable to quickly embark on their Machine Learning journey because these text documents are not labelled. Companies have to invest significant resources to manually label their text documents. Even so, labelling may not be consistent across all documents, as different labellers could be involved.

This tool will speed up your labelling efforts and ensure labelling uniformity. It will assign meaningful tags or categories to short texts according to their content so that recurring and dominant themes can be identified.

Key Features

Able to classify/label short texts

Helps companies kick-start supervised machine learning

Allows efficient labelling

Reduce manpower efforts and time required to label

Ensures uniformity

Reduces subjectivity and allows same labelling process to be applied across text documents

Easy scaling for new labels

Process is easily repeatable if user wants to identify new labels

Step 1.

Collate all documents into one file

Step 2.

Automated pre-processing of file

Step 3.

Create a label dictionary (list of key words that is relevant to specific labels)

Step 4.

Automatically train the auto labeller and apply the labeller!

How It Works

Create an account or login using
your Gmail account. 

Use Cases

Classifying open-ended customer feedback

Type of feedback (e.g. speed of delivery, after-sales services, product defects)

Classifying IT support tickets

Grouping incidents

Classifying emails

Business functions (e.g. marketing, communications, sales, human resource, etc)

Source Repositories

For developers