Learn which natural language processing (NLP) technique – entity recognition, sentiment analysis, key phrase extraction or speech recognition – is used to identify and extract mentions of city names from social media posts. Master key NLP concepts for the AI-900 Microsoft Azure AI Fundamentals certification exam.
Table of Contents
Question
You have a solution that analyzes social media posts to extract the mentions of city names discussed most frequently. Which type of natural language processing (NLP) workload does the solution use?
A. Entity recognition
B. Sentiment analysis
C. Key phrase extraction
D. Speech recognition
Answer
A. Entity recognition
Explanation
Entity recognition, also known as named entity recognition (NER), is a natural language processing (NLP) task that involves identifying and extracting named entities – such as people, organizations, locations, dates, quantities, etc. – from unstructured text data.
In the given scenario, the solution is analyzing social media posts to determine which city names are mentioned most frequently. This is a classic application of entity recognition, where the NLP model would be trained to identify and extract location entities, specifically city names, from the text of the posts.
Entity recognition is the best fit because:
- It deals with unstructured text data (social media posts)
- The goal is to identify and extract a specific type of named entity (city names)
- The extracted entities can then be analyzed to determine frequency of mentions
The other options are not applicable for this use case:
- Sentiment analysis determines the sentiment (positive, negative, neutral) expressed in text, not extracting named entities
- Key phrase extraction identifies the main topics/themes in text, not specific named entities
- Speech recognition converts spoken language to written text, but doesn’t involve entity extraction
Therefore, entity recognition is the NLP technique that would be used in a solution to analyze social media posts and extract the most frequently mentioned city names.
Entity recognition is used to identify and classify key entities, such as city names, within text. In this case, it would help extract and analyze mentions of city names from social media posts.
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