Summary Analyzer

Jibber AI supports extractive summarization.

Extractive summarization is a technique used in natural language processing (NLP) to automatically identify the most important sentences from a text document and present it in a condensed form.

Unlike abstractive summarization, which generates a summary by creating new sentences that capture the meaning of the original text, extractive summarization selects important sentences or passages from the original document and combines them to form a summary.

Extractive summarization involves several steps, including identifying key phrases and sentences, ranking them based on importance, and selecting the top-ranked sentences to form a summary. This technique is widely used in applications such as news article summarization, document summarization, and email summarization.

You can choose how many sentences you would like in the summary.

The response section for summary would look similar to below:

  "summary": {
    "sentences": [
      "My bank account # is 02836886 and sort code is 20-12-55.",
      "I'd like to work for Tesla one day and make electric vehicles.",
      "Can you please wire me £1000 to the IP address"