So if a new label is added, or if the meaning of a label changes, everyone has easy access to the updates.Ĭhecking The Quality Of Your Text Annotations I recommend that you define your labels in a central shared location and keep this information up to date. Usually, there is a team of people that need to agree on what the labels mean. But labels like intent_1, intent_1_ver2, and unnecessary acronyms make it harder to quickly apply and check labels.īesides that, it’s unlikely that one person is going to be annotating everything on their own. food_item and time_of_delivery are good, straightforward labels that describe what you’re annotating. The first thing you can do to make the life of your annotators and developers simple is to keep the labels simple and descriptive. Tips To Make Your Text Annotation Process Better So you might want to annotate that the whole sentence has the intent of placing an order. Then use that piece of information to ensure that you have some brownies for them and that you can deliver them tomorrow. You might want to identify that brownies are a food item and/or that tomorrow is the delivery time. Let’s say you have this piece of text in your corpus: “I am going to order some brownies for tomorrow” This additional information can be used to train machine learning models and to evaluate how well they perform. Text annotation is simply reading natural language data and adding some additional information about it, in a machine-readable format. But if you want to know how well it's doing in production, you'll have to annotate text at some point. And You didn't need to do all the text annotation for training yourself. Maybe you were lucky enough to have a large pre-annotated text corpus. So if you're doing any type of supervised learning in your natural language processing pipeline, and you most likely are, data annotation has played a role in your work. In order for humans to rely on machines, machines need humans first to teach them. Even with all the recent advances in machine learning and artificial intelligence, we can’t escape the irony of the information age.
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