Relevance AI's Editor is an advanced tool designed to facilitate large dataset modifications. This is done by applying a variety of AI-recommended or user-defined rules. The Editor is geared towards editing larger datasets, but also allows for single-entry modification.
- Rule-based editing
- Refine category responses
- Merge and rename categories
Under rule-based editing, users can filter the dataset using a variety of filtering and search option. Then, selected field values can be changed under customisable modification.
In the sample below, we are working on a dataset in which exists a field named "Content". This field has undergone AI-Tagging workflow. But some entries have not been labelled. Here, we are searching for documents that are left untagged and are similar in meaning to "great". The goal is to tag them with "Great App". More information available on Rule based editing.
Under "refine category responses", users can view AI Categories (i.e. Tagging and Clustering) and apply AI recommended modification.
In the sample below, we are looking at tagging results on an App-review dataset. "Premium category is selected, for which AI has recommended 7 modification options.
some of the recommendations are
More information available on Refine category responses.
Under "Merge and rename categories", users can view AI Categories (i.e. Tagging and Clustering), rename them or merge them. "Merge and rename categories" also provides you with AI-recommended merge options.
In the sample below, we are looking at tagging results on an App-review dataset. There is an AI-recommendation for merge. Two tags ("tasks" and "subtask") are manually selected to be merged.
More information available on Merge and rename categories.
Updated about 2 months ago