Core NLP Tasks
Fundamental tasks and applications in Natural Language Processing
Core NLP Tasks
Natural Language Processing encompasses several fundamental tasks that form the building blocks for more complex applications.
Text Classification
Sentiment Analysis
- Binary classification
- Multi-class sentiment
- Aspect-based sentiment
- Emotion detection
Topic Classification
- Document categorization
- News classification
- Intent classification
- Multi-label classification
Named Entity Recognition (NER)
Entity Types
- Person names
- Organizations
- Locations
- Dates and numbers
- Custom entities
Implementation Approaches
- Rule-based systems
- Statistical models
- Deep learning approaches
- Hybrid systems
Part-of-Speech Tagging
POS Categories
- Nouns, verbs, adjectives
- Language-specific tags
- Universal POS tags
- Fine-grained categories
Tagging Methods
- Rule-based tagging
- Statistical taggers
- Neural taggers
- Hybrid approaches
Machine Translation
Translation Approaches
- Statistical MT
- Neural MT
- Hybrid systems
- Zero-shot translation
Challenges
- Language pairs
- Cultural context
- Idiomatic expressions
- Quality evaluation
Text Summarization
Extractive Summarization
- Sentence scoring
- Graph-based methods
- Neural approaches
- Evaluation metrics
Abstractive Summarization
- Sequence-to-sequence models
- Attention mechanisms
- Copy mechanisms
- Beam search
Question Answering
Types of QA Systems
- Factoid QA
- Open-domain QA
- Reading comprehension
- Conversational QA
Implementation Strategies
- Information retrieval
- Neural readers
- Knowledge graphs
- Hybrid approaches
Text Generation
Language Modeling
- N-gram models
- Neural language models
- Transformer-based models
- Evaluation methods
Applications
- Story generation
- Dialog systems
- Code generation
- Text completion
Best Practices
- Data preparation
- Model selection
- Evaluation strategies
- Error analysis
- Performance optimization
Common Challenges
- Data quality
- Model complexity
- Computational resources
- Scalability
- Interpretability
Tools and Frameworks
- spaCy
- NLTK
- Stanford NLP
- Transformers
- AllenNLP
Related Topics
- Text Preprocessing
- Model Architectures
- Evaluation Metrics
- Deployment Strategies