How can I annotate my data efficiently?
Summary
We made the building of an AI model super easy by creating Studio. You have probably already seen on Studio that this is a 4 simple steps process:
Upload Data ---> Define Aspects ---> Annotate Data ---> Start training
After automating the training process, we left only one task for the user: to label, or in other words to annotate, data.
Nevertheless, manual annotation is still a step that demands:
- some background knowledge
- some of your time for its completeness
In this article, you will learn everything you need to know for annotating data quickly, efficiently & correctly.
Text Annotation Guidelines
Annotators help AI models associate text segments to tags (topics & sentiments). To achieve that more efficiently, they should:
- Involve domain experts in the process
- Define topics to be comprehensive and non-overlapping in coverage
- Write definitions for each tag and add examples
- Annotate based on explicit mentions of topics with sentiments (= opinion)
- Ignore implicit and subjective topics and factual statements
- Focus on producing high-quality data, take breaks to refresh focus
- Iterate between annotating and training to speed up the process To shed more light on the process, we mention a few examples
Below you can see how someone can define some aspects in a gsheet efficiently. Firstly, create larger groups to categorize the aspects, and then determine the aspects by providing an example and a description of each case.
To shed more light on the process, we mention below two good practices along with exemplary cases.
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Be careful only to annotate explicitly mentioned topics with sentiments. AI models can only process and learn from the information that is present in the text.
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Try to ignore implicit and subjective or factual segments. Ignoring subjectivity and factual statements improves the quality of the opinion mining model.
Example 1: Facts have no sentiment, so they shouldn’t be annotated.
Example 2: No opinion was explicitly expressed about Delivery.
Example 3 - Not being able to open a bottle makes it not easy to use. It might have a nice design.
Example 4 - The customer received damaged quality. No mention of packaging.