SYSTEMS AND METHODS FOR COMPUTER GENERATION OF A MODIFIABLE PRODUCT DESCRIPTION

Generative language models are able to generate a sequence of text that may closely mimic a native human speaker's own generated text. However, technical challenges exist when implementing a generative language model for generating product descriptions. The model may output certain inaccuracies due to the predictive nature of generating the output. Further, the model does not have the ability to identify words from the product description that a merchant may want to modify, nor the ability to provide meaningful alternatives to such words. In some embodiments, a natural language processor might be built and/or trained using classification data. The natural language processor may identify one or more words and/or phrases in a product description as a candidate for modification. The product description might then be displayed on a merchant-facing user interface with an indication that the candidate for modification may be modified.