You want to find company names and locations in news articles. Which technique fits?
Why A is the answer
Entity recognition
Entity recognition identifies items such as people, places and organizations.
In detail
- Entity recognition finds names, places and similar items.
- Use it to populate search filters.
Use case
An illustrative scenario, not a real incident.
A news monitor finds company names and cities in articles. Entity recognition labels each one.
See it in different ways
flowchart LR A["Text"] --> B["Keyword extraction: main terms"] A --> C["Entity recognition: people, places"] A --> D["Sentiment: positive or negative"] A --> E["Summarization: shorter version"]
mindmap
root((AI workloads))
Text
Sentiment
Key phrases
Entities
Speech
Recognition
Synthesis
Vision
Classification
Object detection
OCR
Documents
Information extraction
Generative
Text
Imagesflowchart LR S0["Article"] --> S1["Entity recognition"] --> S2["Companies"] --> S3["Locations"]
Key point: Names and places come from entity recognition.
Why the other options are wrong
- B. Speech synthesis using a neural voice
- Speech synthesis creates audio.
- C. Sentiment analysis
- Sentiment analysis reads opinion.
- D. Image classification
- Image classification works on images.