Extract Key Phrases from Text Using Azure AI Language

Quick Answer

Key Phrase Extraction is purpose-built to answer a specific question about a piece of text: what is it actually about, expressed as a short list of the main talking points rather than the full sentence structure around them. Feeding a customer review through the API returns the noun phrases and terms it identifies as central to the content, using linguistic analysis to surface what matters, like a specific product feature or a recurring complaint, while filtering out the connective language holding those points together. This is a distinct capability from sentiment analysis, which scores the emotional tone of the text, and from named entity recognition, which identifies specific people, places, or organizations mentioned — Key Phrase Extraction sits alongside those as one of several Azure AI Language features that each answer a different question about the same input text. For a use case like scanning large volumes of customer reviews, Key Phrase Extraction is what turns free-form feedback into scannable topics without needing sentiment scoring or entity identification layered on top, unless the scenario specifically calls for those as well. Any requirement to surface the main topics or terms from unstructured text, as opposed to its tone or named entities, is asking for Key Phrase Extraction.