Abstractive Summarizer
Summarize the following text into [number] sentences using new phrasing while keeping original meaning: [text].
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Tag: nlp
Extractive Summarizer
Summarize the following text by selecting and condensing key sentences only: [text]. Output [number] sentences.
Few-Shot JSON Extractor
Example: Text: ‘Alice, 28, works at DataCorp as a Data Analyst.’ JSON: {“name”: “Alice”, “age”: 28, “company”: “DataCorp”, “title”: “Data Analyst”} Text: [insert text] JSON:
Few-Shot Summarizer
Example: Text: ‘AI is transforming industries through automation, data analysis, and personalization.’ Summary: ‘AI changes industries via automation and personalization.’ Text: [insert text] Summary:
One-Shot Sentiment Classifier
Example: Review: ‘The movie was incredible.’ Sentiment: Positive Review: [insert review] Sentiment:
Entity Extraction Formatter
Extract the following entities from this text: [text]. Format output as: Name: , Role: , Company: , Location: .