Different prepackaged summarization components (extractive and abstractive) are available to compute a short summary of a longer piece of text.
Abstractive Summarization
The algorithm creates an entirely new text, based on the content of the document. Large Language Models are very well fitted for this task.
- Go to the Processing view
- Create a new pipeline
- Select Off-the-shelf component in the drop-down list
- Select a cloud provider of Large Language Models (LLM)
- Select the LLM
- Edit the prompt and write: “Summarize in english the following text: $text“
- Give a name to the “Completion Altext” to store the summary in this metadata field.
- Save your pipeline
- Test it in the Annotation test view as above. See How to test a model?
Extractive Summarization
An algorithm identifies the most informative sentences from a text and brings them together to form the new summary. This approach is quick and easy, but does not generate new sentences which may result in incoherent texts.
- Proceed as above
- Select “textranksummarizer” component
- Adjust available parameters with the settings icon.
- Give a name to the Alternative text (Alttext). The system will generate an additional text field called “ExtrSummary” that holds the newly generated summary.
- Save the pipeline
- Test it in the Test page. See How to test a model?