System

A system comprising:

• circuitry configured to
• receive, via a communication interface coupled to a packet-switched network, image data and supplemental text data from a terminal device,
• preprocess the image data by normalizing pixel values and resizing the image data to a predetermined resolution to generate a multidimensional tensor,
• apply a trained convolutional neural network model to the multidimensional tensor to extract feature information comprising classification information, color attribute information, shape attribute information, and mark attribute information,
• apply a natural language processing algorithm to the supplemental text data to extract phrase-level information and to classify each phrase into at least one of feature information, use-scene information, and advantage information,
• construct, based on the extracted feature information and the classified phrase-level information, a prompt sentence for a generative transformer-based language model, the prompt sentence comprising context information encoding the feature information, designation information identifying template data, and instruction information specifying at least one of a style condition and a length constraint,
• input the prompt sentence to the generative transformer-based language model to cause the generative transformer-based language model to generate candidate text data conforming to a format of the template data,
• generate structured output data by combining the template data, the classified phrase-level information, and the candidate text data, and
• transmit the structured output data to the terminal device for display via a graphical user interface in an editable state.

A method comprising:

• receiving, via a communication interface coupled to a packet-switched network, image data and supplemental text data from a terminal device,
• applying a trained inference model to a multidimensional tensor derived from the image data to extract feature information comprising classification information and attribute information,
• constructing, based on the extracted feature information, a prompt sentence for a generative neural network model, the prompt sentence instructing the generative neural network model to select template data from a plurality of template data records stored in a storage device,
• inputting the prompt sentence to the generative neural network model to cause the generative neural network model to output selection information identifying selected template data,
• generating structured output data by inserting the supplemental text data into the selected template data, and
• transmitting the structured output data to the terminal device for display via a graphical user interface.