Extract Key Information

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Node Inputs

• Text: Text that you want to extract the key information out of. This can be a document loaded from the File Reader, a scraped website, etc.
• Key Information: Define the key information that you want to extract from the text. Each key information item you define should include:
  • Name: The label or identifier for the key information, such as ‘location’.
  • Type: The data type of the information (text, number, boolean). For example, a location would be text, but a temperature would be a number.
  • Description: A brief description of the key information you want to extract, such as ‘The city and state, e.g., San Francisco, CA’.
• Additional Context (Optional): Any additional context or instructions for the information that you are extracting, such as ‘The information that I am extracting is about the location and weather for different cities’.

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Node Output

• List of Key Information: The extracted information based on the criteria defined in the “Key Information” input. This output will be a list containing the extracted pieces of information.

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Node Functionality

This node is designed to take a piece of text and intelligently extract information from it based on criteria you specify. It is an advanced tool that utilizes artificial intelligence to analyze text and find specific pieces of information, like names, locations, or numbers, depending on your needs.

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When To Use

Use the Extract Key Information node when you have a sizable text or document from which you need to extract specific pieces of data automatically. It’s especially useful in scenarios such as:

• Data Analysis and Reporting: When you need to compile reports or conduct analysis based on specific information extracted from large texts or documents.
• Automated Data Extraction: For projects where manual data extraction is too time-consuming or impractical, such as extracting certain types of information from many web pages or documents.
• Information Organization: To automatically categorize and organize information based on specific criteria, improving efficiency and accuracy in data handling processes.
• Content Summarization: When you need to pull out key points or specific details from long articles, research papers, or documents to create concise summaries.

Overall, this node can significantly streamline workflows that require the extraction of specific information from texts, enhancing productivity and accuracy.